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    [title] => FDA OKs World's First AI Solution for Flagging Pulmonary Embolism
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    [summary] => Aidoc now leads the way in FDA approved AI solutions for radiologists.
    [slug] => fda-oks-worlds-first-ai-solution-for-flagging-pulmonary-embolism
    [body] => Aidoc, the provider of AI solutions for radiologists, announced today that it was granted Food and Drug Administration (FDA) clearance for an additional product in its expanding suite of AI-based workflow orchestration solutions. The clearance is for Aidoc's Pulmonary Embolism (PE) solution that works with radiologists to flag and triage PE cases in chest CTs. The approval comes just weeks after Aidoc closed a $27 million funding round, bringing its total funding to $40 million.
 
"In addition to the significant value provided to the department by Aidoc's ICH solution, we recently added the PE module to the workflow," said Dr. Pressman, Chair of Imaging at Cedars-Sinai Medical Center. "I was impressed by the fact that the coverage continuously grows, allowing us to add this product in the workflow of more radiologists, becoming part of our daily work. I was also pleased by the ability of the software to prioritize PE studies accurately."

In the United States alone, Up to 200,000 people a year die due to PE. Undetected or late-detected PE is one of the most common causes of preventable death in hospitalized patients. PE diagnosis can be highly challenging due to its variable and non-specific presentation, making AI-driven workflow triage especially beneficial. Recent research published at ECR in Vienna further shows the accuracy and value Aidoc's solution can provide.
 
"It is clear that AI will play a tremendous role in the future of radiology," said Daniel J. Durand, M.D., Chair of Radiology at LifeBridge Health. "Considering the complexity of vascular diagnosis, we are eager to see how Aidoc's solutions can benefit our pulmonary embolism patients and bring tomorrow's technology to LifeBridge Health, today." LifeBridge Health operates four hospitals in and around Baltimore, Md.
 
The new clearance, combined with Aidoc's other proven solutions, gives Aidoc the most clearances for deep learning solutions in radiology and positions it firmly at the forefront of making AI standard of care.
 
"What really excites us about this clearance is that it paves the way towards scalable product expansion." Elad Walach, Aidoc co-founder and CEO said, "We strive to provide our customers with comprehensive end-to-end solutions and have put a lot of effort in developing a scalable AI platform. It took us 18 months to get our first FDA clearance, 6 for the second one, and we have 8 more packages in active clinical trials, I'm excited about what will come next. I can only extend my utmost gratitude to the FDA for having open communication channels and working together with us on clearing many solutions in parallel."
 
Aidoc's solutions analyze medical images directly after the patient is scanned and notify the radiologists of cases with suspected findings to assist with prioritization of time-sensitive, and potentially life-threatening cases. Aidoc cuts the time from scan to diagnosis for some patients from hours to under five minutes, speeding up treatment and improving prognosis. [views] => 0 [published] => 1 [status] => 3 [priority] => 0 [publish_date] => 2019-05-16 14:21:00 [updated_at] => 2019-05-16 14:29:46 [last_updated_author] => 199474 [uploaded_by] => 199474 [user_role_id] => 0 [custom_fields] => [] [custom_fields_old] => [splitcontent] => 1 [content_url] => [related_content_ids] => ["312909","304193","308911","304315","309324","309318","308079","303655","303607","313969","314230","313865","312820","304505","304247","303994","303895"] [is_show_company_name] => [created_at] => 2019-05-16 14:15:51 [contentType] => ContentType Object ( [className] => ContentType [content] => Array ( ) [taxonomy] => Array ( ) [listURL] => [logoUrl] => https: [id] => 2487 [pageNumber] => [offset] => [totalPages] => [last_query] => [last_sql] => [show_errors] => 1 [databaseServer] => Array ( [key] => master [host] => 172.24.16.232 [user] => rodpub_beta [pass] => MvQQzhse92k58yA [db] => rodpub_beta ) [tableName] => content_types [tag] => breaking_news [short_tag] => breaking_news [class_name] => [display_view] => [list_view] => [slug] => breaking-news [box_view] => [ignore_flag] => 0 [image_id] => 0 [layout_id] => 0 [formattedTag] => Breaking News ) [viewURL] => /contents/view_breaking-news/2019-05-16/fda-oks-worlds-first-ai-solution-for-flagging-pulmonary-embolism/ [relatedArticles] => Array ( [0] => Content Object ( [className] => Content [contentLinks] => Array ( ) [belongsTo] => [contentIssue] => [id] => 303607 [pageNumber] => [offset] => [totalPages] => [last_query] => [last_sql] => [show_errors] => 1 [databaseServer] => Array ( [key] => master [host] => 172.24.16.232 [user] => rodpub_beta [pass] => MvQQzhse92k58yA [db] => rodpub_beta ) [tableName] => contents [content_type_id] => 2487 [resource_id] => 0 [author_id] => 0 [primary_issue_slug] => [author_name] => {"name":"Business Wire","title":""} [magazine_id] => 6 [layout_id] => 0 [primary_image] => 179112 [primary_image_old] => [slider_image_id] => [banner_image] => 0 [title] => TransPerfect Announces EnCompass Rapid Prototyping Program for MDR, IVDR Content Compliance [short_title] => [summary] => Company is partnering with XML content conversion specialist Stilo and information consultant Mekon on program. [slug] => transperfect-announces-encompass-rapid-prototyping-program-for-mdr-ivdr-content-compliance [body] => TransPerfect Medical Device Solutions, the world’s largest provider of language services and process automation technology to the medical device industry, has announced the introduction of its new EnCompass Rapid Prototyping Program. Specifically designed to demonstrate the benefits of XML content management and process automation (including AI-Assist), the EnCompass Prototype Program provides manufacturers with a working model of MDR and IVDR content compliance and cost savings.
 
The Rapid Prototyping Program combines validated content management technology from Astoria Software, process automation technology from TransPerfect, critical conversion technology from Stilo and information development services from leading consultant Mekon.
 
Said Mekon CEO Julian Murfitt, “Our 25 years of expertise with information architecture and automated publishing provides an important benefit for device makers looking to address increased content requirements of MDR and IVDR.”
 
Added Stilo CEO Les Burnham, “Automated content conversion services are especially important as manufacturers migrate to XML-based systems to support the increased volumes and throughput associated with MDR and IVDR.”
 
A Cure for the MDR and IVDR Headache
With only 18 months left before full implementation, the European Union’s new MDR and IVDR are a source of stress and concern for global device makers. The new regulations span a number of operational areas and, according to industry consultant, Qserve, will increase both the volume and velocity of content that device makers must manage.
 
The EnCompass Rapid Prototyping Program provides a low-cost, low-risk approach for device makers to test the benefits of XML content management, automated publication, and translation process automation, (including AI processes) for critical device content: IFUs, software UI, websites, e-learning, clinical data, etc.
 
According to Marc Miller, Division President of TransPerfect Medical Device Solutions, “Faced with substantially increased content volumes due to MDR and IVDR, structured content and automation technologies are emerging as the key components for an effective compliance strategy.”
 
TransPerfect Medical Device Solutions is the specialized medical device division of TransPerfect, the world's largest provider of language services and process automation technology. From offices in more than 90 cities on six continents, TransPerfect offers a full range of services in more than 170 languages to clients worldwide. With a commitment to quality and client service, TransPerfect is fully ISO 9001 and ISO 17100 certified across all offices. The Medical Device Solutions group is further certified to ISO 13485 and ISO 14971.
 
Astoria Software is an award-winning solution for enterprise content management and a division of TransPerfect. Astoria delivers the most comprehensive on-demand solution for building, managing, and assembling DITA/XML content to satisfy documentation requirements in the software, hardware, medical device, and other discreet manufacturing sectors. [views] => 0 [published] => 1 [status] => 3 [priority] => 0 [publish_date] => 2018-12-05 09:04:00 [updated_at] => 2018-12-05 09:11:19 [last_updated_author] => 142087 [uploaded_by] => 142087 [user_role_id] => 0 [custom_fields] => [] [custom_fields_old] => [splitcontent] => 1 [content_url] => [related_content_ids] => ["301046","299739","285594","300075","284024","303655","284243","283959","302323","302922","299952","285042","293867","296469","299801","288799","302836","302385"] [is_show_company_name] => [created_at] => 2019-04-09 04:36:23 ) [1] => Content Object ( [className] => Content [contentLinks] => Array ( ) [belongsTo] => [contentIssue] => [id] => 303655 [pageNumber] => [offset] => [totalPages] => [last_query] => [last_sql] => [show_errors] => 1 [databaseServer] => Array ( [key] => master [host] => 172.24.16.232 [user] => rodpub_beta [pass] => MvQQzhse92k58yA [db] => rodpub_beta ) [tableName] => contents [content_type_id] => 2487 [resource_id] => 0 [author_id] => 0 [primary_issue_slug] => [author_name] => {"name":"PR Newswire","title":""} [magazine_id] => 6 [layout_id] => 0 [primary_image] => 179151 [primary_image_old] => [slider_image_id] => 179151 [banner_image] => 0 [title] => Subtle Medical's SubtlePET Gains FDA Clearance & CE Mark [short_title] => [summary] => SubtlePET is the first AI product cleared for medical imaging enhancement. [slug] => subtle-medicals-subtlepet-gains-fda-clearance-ce-mark [body] => Subtle Medical, a privately-held medical device company focused on improving medical imaging efficiency and patient experience with innovative deep learning imaging technologies, announced today 510(k) clearance from the U.S. Food and Drug Administration (FDA) to market SubtlePET. Subtle Medical also recently secured approval to affix the CE mark on SubtlePET to begin marketing in the European Economic Area without restrictions.
 
SubtlePET's artificial intelligence (AI)-powered technology allows hospitals and imaging centers to enhance images from faster scans leading to an improved patient experience during imaging procedures while boosting exam throughput and provider profitability. SubtlePET is currently in pilot clinical use in multiple university hospitals and imaging centers in the U.S. and abroad.
 
"Focusing Subtle Medical's SubtlePET AI platform on faster image acquisition, we have been able to dramatically increase PET scan efficiency and provide a superior patient experience. SubtlePET technology allows us to scan a patient four times faster than normal, yet maintain equal image quality, not otherwise impacting workflow," said Michael Brant-Zawadzki, M.D., FACR, Hoag Hospital, Newport Beach, Calif. "This creates immediate ROI benefit for our hospital and a compelling value proposition. I'm looking forward to seeing more groundbreaking technology from the Subtle team."
 
Subtle Medical's AI solution enables completion of more exams in a day compared to conventional PET imaging without the need for capital expenditures. It reduces patient time in the scanner and helps hospitals and imaging centers enhance their bottom line in today's competitive healthcare environment. The company's technology utilizes deep learning algorithms that integrate seamlessly with any OEM scanner and PACS system to enhance images during acquisition without any interruption or alteration in the imaging specialists' workflow. SubtlePET delivers a significant improvement in the image quality of noisy images resulting from shorter scans, which is particularly beneficial for children and those undergoing repeat PET exams.
 
SubtlePET is the first product in Subtle Medical's growing portfolio of new AI technologies to receive FDA clearance. "This FDA clearance is a key milestone in Subtle Medical's mission to bring novel and empathetic deep learning to improve patient satisfaction," said Enhao Gong, Ph.D., founder and CEO of Subtle Medical. "The accomplishment of having the first AI cleared for use in nuclear medicine applications validates our team's strength and the commitment of our collaborators. Our focus on image acquisition and workflow differentiates us from other AI companies that are working on post-processing and computer-aided diagnosis products. We are not replacing radiologists--we are addressing the tremendous cost to U.S. healthcare by leveraging deep learning in imaging at the infrastructure level to enable better and higher quality care."
 
Subtle Medical is developing additional products to be submitted for FDA clearance. A second product currently undergoing clinical evaluation is SubtleMR, which allows imaging centers to significantly accelerate MRI scans using the company's AI solutions. SubtleGAD is also being developed to reduce gadolinium dosage during imaging procedures.
 
In March 2018, Subtle Medical received the NVIDIA Inception Award for Top Healthcare+AI Startup Globally selected from over 3,000 AI contenders. The company was also selected as the first AI+healthcare startup for Bessemer Venture Partners' Deep Health Seed Program. Most recently, it was named as a 2018 Minnies Award semi-finalist for Best New Radiology Vendor by AuntMinnie.com. [views] => 0 [published] => 1 [status] => 3 [priority] => 0 [publish_date] => 2018-12-05 10:47:00 [updated_at] => 2018-12-05 10:53:53 [last_updated_author] => 199474 [uploaded_by] => 199474 [user_role_id] => 0 [custom_fields] => [] [custom_fields_old] => [splitcontent] => 1 [content_url] => [related_content_ids] => ["301046","299739","285594","300075","284024","284243","283959","303607","301783","289755","300325","299507","293406","283958","299399","299785","302305","300186"] [is_show_company_name] => [created_at] => 2019-04-09 04:36:23 ) [2] => Content Object ( [className] => Content [contentLinks] => Array ( ) [belongsTo] => [contentIssue] => [id] => 303895 [pageNumber] => [offset] => [totalPages] => [last_query] => [last_sql] => [show_errors] => 1 [databaseServer] => Array ( [key] => master [host] => 172.24.16.232 [user] => rodpub_beta [pass] => MvQQzhse92k58yA [db] => rodpub_beta ) [tableName] => contents [content_type_id] => 2487 [resource_id] => 0 [author_id] => 0 [primary_issue_slug] => [author_name] => {"name":"GlobeNewswire","title":""} [magazine_id] => 6 [layout_id] => 0 [primary_image] => 179332 [primary_image_old] => [slider_image_id] => [banner_image] => 0 [title] => FDA Clears iCAD's ProFound AI for Digital Breast Tomosynthesis [short_title] => [summary] => ProFound AI is a high-performance, deep-learning, cancer detection and workflow solution for DBT. [slug] => fda-clears-icads-profound-ai-for-digital-breast-tomosynthesis [body] => iCAD Inc., a developer of cancer detection and therapy solutions, announced clearance by the United States Food and Drug Administration (FDA) for their latest, deep-learning, cancer detection software solution for digital breast tomosynthesis (DBT), ProFound AI, clearing the technology for commercial sales and clinical use in the United States. The powerful solution built on artificial intelligence (AI) is now available to healthcare facilities in the U.S., providing access to the most cutting-edge breast cancer detection software in the marketplace today.
 
“Obtaining FDA clearance for ProFound AI opens a new and substantial addressable market for iCAD. This enables us to offer clinicians globally an unrivaled cancer detection and workflow solution built on the latest advances in deep-learning,” said Stacey Stevens, executive vice president and chief strategy and commercial officer at iCAD. “Clinical reader study results and comprehensive stand-alone testing have shown unprecedented improvements in both clinical performance and reading efficiency. We are proud to introduce revolutionary technology that will fundamentally transform breast cancer detection and patient care.”
 
The FDA clearance is based on positive clinical results from a large reader study completed earlier this year and presented at this year’s Radiological Society of North America (RSNA) annual meeting at McCormick Place in Chicago. The research was performed with 24 radiologists who read 260 tomosynthesis cases both with and without iCAD’s ProFound AI solution. The findings show impressive results including increased cancer detection rates, reduced false positive rates and patient recalls, and a significant decrease in interpretation times.
 
“This technology shows tremendous promise in assisting radiologists in detecting cancers, reducing recalls and increasing efficiency when reading tomosynthesis studies,” said Emily Conant, M.D., Professor and Chief, Division of Breast Imaging, Vice Chair of Faculty Development, Department of Radiology at the Hospital of the University of Pennsylvania. “Clinical data shows that when tomosynthesis readers use the ProFound AI algorithm, case-level sensitivity is improved by 8 percent on average and reading times are significantly decreased. Radiologists with various levels of expertise may benefit from this AI-driven technology when reading large tomosynthesis data sets.”
 
ProFound AI is a high-performance, deep-learning, cancer detection and workflow solution for DBT delivering critical benefits to radiologists, their facilities, and their patients through improvement of cancer detection rates by an average of 8 percent and decreasing unnecessary patient recall rates by an average of 7 percent. The new technology is trained to detect malignant soft-tissue densities and calcifications. It also provides radiologists with scoring information representing the likelihood that a detection or case is malignant based on the large dataset of clinical images used to train the algorithm.
 
In addition to improving clinical performance related to breast cancer detection and false positive rates, study results showed that ProFound AI can reduce radiologists’ reading time by more than 50 percent on average. An increase in reading time has been a significant challenge for radiologists when moving from 2D to 3D mammography.
 
The solution is currently available for use with leading DBT systems in the U.S., Canada, and Europe. [views] => 0 [published] => 1 [status] => 3 [priority] => 0 [publish_date] => 2018-12-07 10:22:00 [updated_at] => 2018-12-07 10:32:01 [last_updated_author] => 199474 [uploaded_by] => 199474 [user_role_id] => 0 [custom_fields] => [] [custom_fields_old] => [splitcontent] => 1 [content_url] => [related_content_ids] => ["303655","300325","299507","293406","283958","289755","299399","299785","285594","302305","300780","298542","297184","297010","290992","290172","289956","288233","287718","287547"] [is_show_company_name] => [created_at] => 2019-04-09 04:36:23 ) [3] => Content Object ( [className] => Content [contentLinks] => Array ( ) [belongsTo] => [contentIssue] => [id] => 303994 [pageNumber] => [offset] => [totalPages] => [last_query] => [last_sql] => [show_errors] => 1 [databaseServer] => Array ( [key] => master [host] => 172.24.16.232 [user] => rodpub_beta [pass] => MvQQzhse92k58yA [db] => rodpub_beta ) [tableName] => contents [content_type_id] => 2487 [resource_id] => 0 [author_id] => 0 [primary_issue_slug] => [author_name] => {"name":"Business Wire","title":""} [magazine_id] => 6 [layout_id] => 0 [primary_image] => 179392 [primary_image_old] => [slider_image_id] => 179392 [banner_image] => 0 [title] => Bay Labs and Edwards Partner on AI Software to Improve Heart Disease Detection [short_title] => [summary] => Among other initiatives, Bay Labs will integrate its EchoMD measurement and interpretation software into Edwards’ CardioCare quality care navigation platform. [slug] => bay-labs-and-edwards-partner-on-ai-software-to-improve-heart-disease-detection [body] => Bay Labs, a medical technology company at the forefront of applying artificial intelligence (AI) to cardiovascular imaging, announced today a collaboration with Edwards Lifesciences focused on improving the detection of heart disease. The partnership involves multiple initiatives, including the development of new AI-powered algorithms in Bay Labs’ EchoMD measurement and interpretation software suite, the integration of EchoMD algorithms into Edwards Lifesciences’ CardioCare quality care navigation platform, and support for ongoing clinical studies at leading institutions.
 
Multiple EchoMD algorithms have been integrated into the CardioCare platform for investigational use to retrospectively analyze echocardiograms. The companies believe that incorporating these and future algorithms into clinical practice could help drive quality improvement and potentially increase accurate heart disease detection.
 
“Our vision is to improve patient care throughout the continuum from disease detection to appropriate intervention,” said Charles Cadieu, co-founder and CEO of Bay Labs. “Working with Edwards to deploy Bay Labs’ AI software with deep learning technology into clinical settings has the potential to derive quality improvements and to increase the accuracy of timely heart disease detection.”
 
“Improving detection of disease starts with better quality echoes,” said Dr. Madalina Petrescu, director of echocardiographic laboratory, Swedish Hospital. “CardioCare helps to reduce variability in echoes, and I believe Bay Labs’ AI technology has the potential to impact patient lives, namely by improving the accuracy of disease detection and diagnosis.”
 
The CardioCare program combines clinical consulting expertise with a cloud-based platform to facilitate the identification, referral, and care pathway management of patients with structural heart disease. CardioCare can help hospitals improve quality by reducing variability in echocardiography and ensure effective communication between care settings to ensure patients access to care. The EchoMD software suite assists cardiologists in automated review of images captured during echocardiograms.
 
Bay Labs received FDA clearance for its first release of EchoMD in June 2018, which included AutoEF. AutoEF automates the calculation of left ventricular ejection fraction (EF), the single most widely used measurement of cardiac function.
 
AutoEF relies on an Image Quality Score algorithm which quantifies the image quality of echo clips and enables display of the quality level alongside relevant images.
 
“It is unfortunate that patients suffering from severe aortic stenosis frequently do not receive a proper diagnosis, for a variety of reasons,” said Don Bobo, Edwards’ corporate vice president, strategy and corporate development. “The value of Bay Labs’ technology is in providing help for these patients to be appropriately diagnosed and successfully find their way to proper treatments.”
 
According to a 2014 publication from the American Heart Association, aortic valve stenosis is one of the most common valvular diseases and is the third most common cardiovascular disease in developed countries. Earlier detection of heart disease, using tools like echocardiography, may lead to more appropriate treatment for these patients. [views] => 0 [published] => 1 [status] => 3 [priority] => 0 [publish_date] => 2018-12-10 09:59:00 [updated_at] => 2018-12-10 10:07:48 [last_updated_author] => 199474 [uploaded_by] => 199474 [user_role_id] => 0 [custom_fields] => [] [custom_fields_old] => [splitcontent] => 1 [content_url] => [related_content_ids] => ["283958","299399","299639","289791","300637","294049","303655","300325","299507","293406","289755","303895","299785","285594"] [is_show_company_name] => [created_at] => 2019-04-09 04:36:23 ) [4] => Content Object ( [className] => Content [contentLinks] => Array ( ) [belongsTo] => [contentIssue] => [id] => 304193 [pageNumber] => [offset] => [totalPages] => [last_query] => [last_sql] => [show_errors] => 1 [databaseServer] => Array ( [key] => master [host] => 172.24.16.232 [user] => rodpub_beta [pass] => MvQQzhse92k58yA [db] => rodpub_beta ) [tableName] => contents [content_type_id] => 2487 [resource_id] => 0 [author_id] => 0 [primary_issue_slug] => [author_name] => {"name":"Brigham and Womens Hospital","title":""} [magazine_id] => 6 [layout_id] => 0 [primary_image] => 179537 [primary_image_old] => [slider_image_id] => 179537 [banner_image] => 0 [title] => Smartphone-Based Test Detects Signs of Ovulation in Saliva [short_title] => [summary] => The artificial intelligence software correctly identified ovulation in 99 percent of samples. [slug] => smartphone-based-test-detects-signs-of-ovulation-in-saliva [body] => Investigators from Brigham and Women's Hospital are developing an automated, low-cost tool to predict a woman's ovulation and aid in family planning. Capitalizing on advancements in several areas, including microfluidics, artificial intelligence (AI) and the ubiquity of smartphones, the team has built an ovulation testing tool that can automatically detect fern patterns—a marker of ovulation—in a saliva sample. The team evaluated the performance of the device using artificial saliva in the lab and validated results in human saliva samples from six subjects, observing greater than 99 percent accuracy in effectively predicting ovulation. The team's results are published in Lab on a Chip.
 
"Before we started this project, we weren't aware that such a need existed. When we published last year on a technology for analyzing sperm to detect male infertility, we were approached by those who had read about our work and were wondering if we could develop a smart-phone based system to provide ovulation testing at home," said corresponding author Hadi Shafiee, Ph.D., principal investigator at the BWH Division of Engineering in Medicine and Renal Division of Medicine. "Our study indicates that an accurate, automated and low-cost test is indeed possible."
 
Current methods for monitoring woman's fertility are often costly or subjective. These methods include ovulation detection through luteinizing hormone (LH) level determination (a clinical blood test or at-home urine "dip stick" test), rectal or basal body temperature analysis, cervical mucus characterization and salivary ferning analysis. Salivary ferning refers to the unique appearance of dried saliva from a woman who is ovulating—when collected on a glass slide, saliva takes on a crystallized structure that resembles fern leaves. While relatively inexpensive and simple, salivary fern analysis is highly subjective; when performed by the lay consumer, this approach is prone to misinterpretation.
 
To overcome this challenge, Shafiee and colleagues developed an automated process for detecting ferning in a saliva sample. The developed AI algorithm was pre-trained with 1.4 million ImageNet images and retrained with more than 1500 salivary ferning images to be able to classify saliva images into two categories: Ovulating and non-ovulating samples.
 
The team then evaluated the system's ability to differentiate ovulating and non-ovulating human saliva samples from six subjects. The women collected and tested their saliva samples using the cell phone system during both ovulating and non-ovulating phases of their menstrual cycle (results were confirmed using a urine test). To perform the test, saliva was collected on a microfluidic device, smeared, and left to air dry. The microfluidic device with the air-dried sample was then inserted into a 3D printed optical attachment affixed to a smartphone. The software then analyzed the fern patterns, correctly identifying ovulation in 99 percent of samples and non-ovulation in 100 percent of the samples.
 
"One of the biggest advantages to this method is cost—whereas the cost of non-reusable urine stick tests can add up to $210 to $240 over the course of six months, our device represents the possibility of a one-time purchase," said co-author Manoj Kumar Kanakasabapathy, a senior research assistant in the Shafiee laboratory. "Beyond human ovulation, there are applications here as well for animal breeding and even for dry eye disease, which can also produce fern-like patterns in samples from eye mucosa."
 
"One of the biggest problems with saliva-based tests, we realized, was that users find it difficult to interpret the fern patterns," said Prudhvi Thirumalaraju, another co-author of this study and a senior research assistant in Shafiee's laboratory. "We figured that advances in AI can be put to good use here, to help people get objective results on their smartphones."
 
The new system is constrained by some of the same limitations as traditional ovulation tests, and cannot detect ovulation in women with estrogen imbalance, cysts in the ovaries, and those who take fertility medications. Smoking or alcohol consumption may also interfere with accurate detection. The device will require additional testing in a larger population and approval by the Federal Drug Administration before it can be brought to market. [views] => 0 [published] => 1 [status] => 3 [priority] => 0 [publish_date] => 2018-12-13 09:00:00 [updated_at] => 2018-12-13 09:05:52 [last_updated_author] => 199474 [uploaded_by] => 199474 [user_role_id] => 0 [custom_fields] => [] [custom_fields_old] => [splitcontent] => 1 [content_url] => [related_content_ids] => ["301046","299739","285594","300075","284024","303655","284243","283959","303607","285017","304247","303994","300325","299507","293406","283958","289755","303895","299399"] [is_show_company_name] => [created_at] => 2019-04-09 04:36:23 ) ) [relatedContent] => Array ( [0] => Content Object ( [className] => Content [contentLinks] => Array ( ) [belongsTo] => [contentIssue] => [id] => 303607 [pageNumber] => [offset] => [totalPages] => [last_query] => [last_sql] => [show_errors] => 1 [databaseServer] => Array ( [key] => master [host] => 172.24.16.232 [user] => rodpub_beta [pass] => MvQQzhse92k58yA [db] => rodpub_beta ) [tableName] => contents [content_type_id] => 2487 [resource_id] => 0 [author_id] => 0 [primary_issue_slug] => [author_name] => {"name":"Business Wire","title":""} [magazine_id] => 6 [layout_id] => 0 [primary_image] => 179112 [primary_image_old] => [slider_image_id] => [banner_image] => 0 [title] => TransPerfect Announces EnCompass Rapid Prototyping Program for MDR, IVDR Content Compliance [short_title] => [summary] => Company is partnering with XML content conversion specialist Stilo and information consultant Mekon on program. [slug] => transperfect-announces-encompass-rapid-prototyping-program-for-mdr-ivdr-content-compliance [body] => TransPerfect Medical Device Solutions, the world’s largest provider of language services and process automation technology to the medical device industry, has announced the introduction of its new EnCompass Rapid Prototyping Program. Specifically designed to demonstrate the benefits of XML content management and process automation (including AI-Assist), the EnCompass Prototype Program provides manufacturers with a working model of MDR and IVDR content compliance and cost savings.
 
The Rapid Prototyping Program combines validated content management technology from Astoria Software, process automation technology from TransPerfect, critical conversion technology from Stilo and information development services from leading consultant Mekon.
 
Said Mekon CEO Julian Murfitt, “Our 25 years of expertise with information architecture and automated publishing provides an important benefit for device makers looking to address increased content requirements of MDR and IVDR.”
 
Added Stilo CEO Les Burnham, “Automated content conversion services are especially important as manufacturers migrate to XML-based systems to support the increased volumes and throughput associated with MDR and IVDR.”
 
A Cure for the MDR and IVDR Headache
With only 18 months left before full implementation, the European Union’s new MDR and IVDR are a source of stress and concern for global device makers. The new regulations span a number of operational areas and, according to industry consultant, Qserve, will increase both the volume and velocity of content that device makers must manage.
 
The EnCompass Rapid Prototyping Program provides a low-cost, low-risk approach for device makers to test the benefits of XML content management, automated publication, and translation process automation, (including AI processes) for critical device content: IFUs, software UI, websites, e-learning, clinical data, etc.
 
According to Marc Miller, Division President of TransPerfect Medical Device Solutions, “Faced with substantially increased content volumes due to MDR and IVDR, structured content and automation technologies are emerging as the key components for an effective compliance strategy.”
 
TransPerfect Medical Device Solutions is the specialized medical device division of TransPerfect, the world's largest provider of language services and process automation technology. From offices in more than 90 cities on six continents, TransPerfect offers a full range of services in more than 170 languages to clients worldwide. With a commitment to quality and client service, TransPerfect is fully ISO 9001 and ISO 17100 certified across all offices. The Medical Device Solutions group is further certified to ISO 13485 and ISO 14971.
 
Astoria Software is an award-winning solution for enterprise content management and a division of TransPerfect. Astoria delivers the most comprehensive on-demand solution for building, managing, and assembling DITA/XML content to satisfy documentation requirements in the software, hardware, medical device, and other discreet manufacturing sectors. [views] => 0 [published] => 1 [status] => 3 [priority] => 0 [publish_date] => 2018-12-05 09:04:00 [updated_at] => 2018-12-05 09:11:19 [last_updated_author] => 142087 [uploaded_by] => 142087 [user_role_id] => 0 [custom_fields] => [] [custom_fields_old] => [splitcontent] => 1 [content_url] => [related_content_ids] => ["301046","299739","285594","300075","284024","303655","284243","283959","302323","302922","299952","285042","293867","296469","299801","288799","302836","302385"] [is_show_company_name] => [created_at] => 2019-04-09 04:36:23 ) [1] => Content Object ( [className] => Content [contentLinks] => Array ( ) [belongsTo] => [contentIssue] => [id] => 303655 [pageNumber] => [offset] => [totalPages] => [last_query] => [last_sql] => [show_errors] => 1 [databaseServer] => Array ( [key] => master [host] => 172.24.16.232 [user] => rodpub_beta [pass] => MvQQzhse92k58yA [db] => rodpub_beta ) [tableName] => contents [content_type_id] => 2487 [resource_id] => 0 [author_id] => 0 [primary_issue_slug] => [author_name] => {"name":"PR Newswire","title":""} [magazine_id] => 6 [layout_id] => 0 [primary_image] => 179151 [primary_image_old] => [slider_image_id] => 179151 [banner_image] => 0 [title] => Subtle Medical's SubtlePET Gains FDA Clearance & CE Mark [short_title] => [summary] => SubtlePET is the first AI product cleared for medical imaging enhancement. [slug] => subtle-medicals-subtlepet-gains-fda-clearance-ce-mark [body] => Subtle Medical, a privately-held medical device company focused on improving medical imaging efficiency and patient experience with innovative deep learning imaging technologies, announced today 510(k) clearance from the U.S. Food and Drug Administration (FDA) to market SubtlePET. Subtle Medical also recently secured approval to affix the CE mark on SubtlePET to begin marketing in the European Economic Area without restrictions.
 
SubtlePET's artificial intelligence (AI)-powered technology allows hospitals and imaging centers to enhance images from faster scans leading to an improved patient experience during imaging procedures while boosting exam throughput and provider profitability. SubtlePET is currently in pilot clinical use in multiple university hospitals and imaging centers in the U.S. and abroad.
 
"Focusing Subtle Medical's SubtlePET AI platform on faster image acquisition, we have been able to dramatically increase PET scan efficiency and provide a superior patient experience. SubtlePET technology allows us to scan a patient four times faster than normal, yet maintain equal image quality, not otherwise impacting workflow," said Michael Brant-Zawadzki, M.D., FACR, Hoag Hospital, Newport Beach, Calif. "This creates immediate ROI benefit for our hospital and a compelling value proposition. I'm looking forward to seeing more groundbreaking technology from the Subtle team."
 
Subtle Medical's AI solution enables completion of more exams in a day compared to conventional PET imaging without the need for capital expenditures. It reduces patient time in the scanner and helps hospitals and imaging centers enhance their bottom line in today's competitive healthcare environment. The company's technology utilizes deep learning algorithms that integrate seamlessly with any OEM scanner and PACS system to enhance images during acquisition without any interruption or alteration in the imaging specialists' workflow. SubtlePET delivers a significant improvement in the image quality of noisy images resulting from shorter scans, which is particularly beneficial for children and those undergoing repeat PET exams.
 
SubtlePET is the first product in Subtle Medical's growing portfolio of new AI technologies to receive FDA clearance. "This FDA clearance is a key milestone in Subtle Medical's mission to bring novel and empathetic deep learning to improve patient satisfaction," said Enhao Gong, Ph.D., founder and CEO of Subtle Medical. "The accomplishment of having the first AI cleared for use in nuclear medicine applications validates our team's strength and the commitment of our collaborators. Our focus on image acquisition and workflow differentiates us from other AI companies that are working on post-processing and computer-aided diagnosis products. We are not replacing radiologists--we are addressing the tremendous cost to U.S. healthcare by leveraging deep learning in imaging at the infrastructure level to enable better and higher quality care."
 
Subtle Medical is developing additional products to be submitted for FDA clearance. A second product currently undergoing clinical evaluation is SubtleMR, which allows imaging centers to significantly accelerate MRI scans using the company's AI solutions. SubtleGAD is also being developed to reduce gadolinium dosage during imaging procedures.
 
In March 2018, Subtle Medical received the NVIDIA Inception Award for Top Healthcare+AI Startup Globally selected from over 3,000 AI contenders. The company was also selected as the first AI+healthcare startup for Bessemer Venture Partners' Deep Health Seed Program. Most recently, it was named as a 2018 Minnies Award semi-finalist for Best New Radiology Vendor by AuntMinnie.com. [views] => 0 [published] => 1 [status] => 3 [priority] => 0 [publish_date] => 2018-12-05 10:47:00 [updated_at] => 2018-12-05 10:53:53 [last_updated_author] => 199474 [uploaded_by] => 199474 [user_role_id] => 0 [custom_fields] => [] [custom_fields_old] => [splitcontent] => 1 [content_url] => [related_content_ids] => ["301046","299739","285594","300075","284024","284243","283959","303607","301783","289755","300325","299507","293406","283958","299399","299785","302305","300186"] [is_show_company_name] => [created_at] => 2019-04-09 04:36:23 ) [2] => Content Object ( [className] => Content [contentLinks] => Array ( ) [belongsTo] => [contentIssue] => [id] => 303895 [pageNumber] => [offset] => [totalPages] => [last_query] => [last_sql] => [show_errors] => 1 [databaseServer] => Array ( [key] => master [host] => 172.24.16.232 [user] => rodpub_beta [pass] => MvQQzhse92k58yA [db] => rodpub_beta ) [tableName] => contents [content_type_id] => 2487 [resource_id] => 0 [author_id] => 0 [primary_issue_slug] => [author_name] => {"name":"GlobeNewswire","title":""} [magazine_id] => 6 [layout_id] => 0 [primary_image] => 179332 [primary_image_old] => [slider_image_id] => [banner_image] => 0 [title] => FDA Clears iCAD's ProFound AI for Digital Breast Tomosynthesis [short_title] => [summary] => ProFound AI is a high-performance, deep-learning, cancer detection and workflow solution for DBT. [slug] => fda-clears-icads-profound-ai-for-digital-breast-tomosynthesis [body] => iCAD Inc., a developer of cancer detection and therapy solutions, announced clearance by the United States Food and Drug Administration (FDA) for their latest, deep-learning, cancer detection software solution for digital breast tomosynthesis (DBT), ProFound AI, clearing the technology for commercial sales and clinical use in the United States. The powerful solution built on artificial intelligence (AI) is now available to healthcare facilities in the U.S., providing access to the most cutting-edge breast cancer detection software in the marketplace today.
 
“Obtaining FDA clearance for ProFound AI opens a new and substantial addressable market for iCAD. This enables us to offer clinicians globally an unrivaled cancer detection and workflow solution built on the latest advances in deep-learning,” said Stacey Stevens, executive vice president and chief strategy and commercial officer at iCAD. “Clinical reader study results and comprehensive stand-alone testing have shown unprecedented improvements in both clinical performance and reading efficiency. We are proud to introduce revolutionary technology that will fundamentally transform breast cancer detection and patient care.”
 
The FDA clearance is based on positive clinical results from a large reader study completed earlier this year and presented at this year’s Radiological Society of North America (RSNA) annual meeting at McCormick Place in Chicago. The research was performed with 24 radiologists who read 260 tomosynthesis cases both with and without iCAD’s ProFound AI solution. The findings show impressive results including increased cancer detection rates, reduced false positive rates and patient recalls, and a significant decrease in interpretation times.
 
“This technology shows tremendous promise in assisting radiologists in detecting cancers, reducing recalls and increasing efficiency when reading tomosynthesis studies,” said Emily Conant, M.D., Professor and Chief, Division of Breast Imaging, Vice Chair of Faculty Development, Department of Radiology at the Hospital of the University of Pennsylvania. “Clinical data shows that when tomosynthesis readers use the ProFound AI algorithm, case-level sensitivity is improved by 8 percent on average and reading times are significantly decreased. Radiologists with various levels of expertise may benefit from this AI-driven technology when reading large tomosynthesis data sets.”
 
ProFound AI is a high-performance, deep-learning, cancer detection and workflow solution for DBT delivering critical benefits to radiologists, their facilities, and their patients through improvement of cancer detection rates by an average of 8 percent and decreasing unnecessary patient recall rates by an average of 7 percent. The new technology is trained to detect malignant soft-tissue densities and calcifications. It also provides radiologists with scoring information representing the likelihood that a detection or case is malignant based on the large dataset of clinical images used to train the algorithm.
 
In addition to improving clinical performance related to breast cancer detection and false positive rates, study results showed that ProFound AI can reduce radiologists’ reading time by more than 50 percent on average. An increase in reading time has been a significant challenge for radiologists when moving from 2D to 3D mammography.
 
The solution is currently available for use with leading DBT systems in the U.S., Canada, and Europe. [views] => 0 [published] => 1 [status] => 3 [priority] => 0 [publish_date] => 2018-12-07 10:22:00 [updated_at] => 2018-12-07 10:32:01 [last_updated_author] => 199474 [uploaded_by] => 199474 [user_role_id] => 0 [custom_fields] => [] [custom_fields_old] => [splitcontent] => 1 [content_url] => [related_content_ids] => ["303655","300325","299507","293406","283958","289755","299399","299785","285594","302305","300780","298542","297184","297010","290992","290172","289956","288233","287718","287547"] [is_show_company_name] => [created_at] => 2019-04-09 04:36:23 ) [3] => Content Object ( [className] => Content [contentLinks] => Array ( ) [belongsTo] => [contentIssue] => [id] => 303994 [pageNumber] => [offset] => [totalPages] => [last_query] => [last_sql] => [show_errors] => 1 [databaseServer] => Array ( [key] => master [host] => 172.24.16.232 [user] => rodpub_beta [pass] => MvQQzhse92k58yA [db] => rodpub_beta ) [tableName] => contents [content_type_id] => 2487 [resource_id] => 0 [author_id] => 0 [primary_issue_slug] => [author_name] => {"name":"Business Wire","title":""} [magazine_id] => 6 [layout_id] => 0 [primary_image] => 179392 [primary_image_old] => [slider_image_id] => 179392 [banner_image] => 0 [title] => Bay Labs and Edwards Partner on AI Software to Improve Heart Disease Detection [short_title] => [summary] => Among other initiatives, Bay Labs will integrate its EchoMD measurement and interpretation software into Edwards’ CardioCare quality care navigation platform. [slug] => bay-labs-and-edwards-partner-on-ai-software-to-improve-heart-disease-detection [body] => Bay Labs, a medical technology company at the forefront of applying artificial intelligence (AI) to cardiovascular imaging, announced today a collaboration with Edwards Lifesciences focused on improving the detection of heart disease. The partnership involves multiple initiatives, including the development of new AI-powered algorithms in Bay Labs’ EchoMD measurement and interpretation software suite, the integration of EchoMD algorithms into Edwards Lifesciences’ CardioCare quality care navigation platform, and support for ongoing clinical studies at leading institutions.
 
Multiple EchoMD algorithms have been integrated into the CardioCare platform for investigational use to retrospectively analyze echocardiograms. The companies believe that incorporating these and future algorithms into clinical practice could help drive quality improvement and potentially increase accurate heart disease detection.
 
“Our vision is to improve patient care throughout the continuum from disease detection to appropriate intervention,” said Charles Cadieu, co-founder and CEO of Bay Labs. “Working with Edwards to deploy Bay Labs’ AI software with deep learning technology into clinical settings has the potential to derive quality improvements and to increase the accuracy of timely heart disease detection.”
 
“Improving detection of disease starts with better quality echoes,” said Dr. Madalina Petrescu, director of echocardiographic laboratory, Swedish Hospital. “CardioCare helps to reduce variability in echoes, and I believe Bay Labs’ AI technology has the potential to impact patient lives, namely by improving the accuracy of disease detection and diagnosis.”
 
The CardioCare program combines clinical consulting expertise with a cloud-based platform to facilitate the identification, referral, and care pathway management of patients with structural heart disease. CardioCare can help hospitals improve quality by reducing variability in echocardiography and ensure effective communication between care settings to ensure patients access to care. The EchoMD software suite assists cardiologists in automated review of images captured during echocardiograms.
 
Bay Labs received FDA clearance for its first release of EchoMD in June 2018, which included AutoEF. AutoEF automates the calculation of left ventricular ejection fraction (EF), the single most widely used measurement of cardiac function.
 
AutoEF relies on an Image Quality Score algorithm which quantifies the image quality of echo clips and enables display of the quality level alongside relevant images.
 
“It is unfortunate that patients suffering from severe aortic stenosis frequently do not receive a proper diagnosis, for a variety of reasons,” said Don Bobo, Edwards’ corporate vice president, strategy and corporate development. “The value of Bay Labs’ technology is in providing help for these patients to be appropriately diagnosed and successfully find their way to proper treatments.”
 
According to a 2014 publication from the American Heart Association, aortic valve stenosis is one of the most common valvular diseases and is the third most common cardiovascular disease in developed countries. Earlier detection of heart disease, using tools like echocardiography, may lead to more appropriate treatment for these patients. [views] => 0 [published] => 1 [status] => 3 [priority] => 0 [publish_date] => 2018-12-10 09:59:00 [updated_at] => 2018-12-10 10:07:48 [last_updated_author] => 199474 [uploaded_by] => 199474 [user_role_id] => 0 [custom_fields] => [] [custom_fields_old] => [splitcontent] => 1 [content_url] => [related_content_ids] => ["283958","299399","299639","289791","300637","294049","303655","300325","299507","293406","289755","303895","299785","285594"] [is_show_company_name] => [created_at] => 2019-04-09 04:36:23 ) [4] => Content Object ( [className] => Content [contentLinks] => Array ( ) [belongsTo] => [contentIssue] => [id] => 304193 [pageNumber] => [offset] => [totalPages] => [last_query] => [last_sql] => [show_errors] => 1 [databaseServer] => Array ( [key] => master [host] => 172.24.16.232 [user] => rodpub_beta [pass] => MvQQzhse92k58yA [db] => rodpub_beta ) [tableName] => contents [content_type_id] => 2487 [resource_id] => 0 [author_id] => 0 [primary_issue_slug] => [author_name] => {"name":"Brigham and Womens Hospital","title":""} [magazine_id] => 6 [layout_id] => 0 [primary_image] => 179537 [primary_image_old] => [slider_image_id] => 179537 [banner_image] => 0 [title] => Smartphone-Based Test Detects Signs of Ovulation in Saliva [short_title] => [summary] => The artificial intelligence software correctly identified ovulation in 99 percent of samples. [slug] => smartphone-based-test-detects-signs-of-ovulation-in-saliva [body] => Investigators from Brigham and Women's Hospital are developing an automated, low-cost tool to predict a woman's ovulation and aid in family planning. Capitalizing on advancements in several areas, including microfluidics, artificial intelligence (AI) and the ubiquity of smartphones, the team has built an ovulation testing tool that can automatically detect fern patterns—a marker of ovulation—in a saliva sample. The team evaluated the performance of the device using artificial saliva in the lab and validated results in human saliva samples from six subjects, observing greater than 99 percent accuracy in effectively predicting ovulation. The team's results are published in Lab on a Chip.
 
"Before we started this project, we weren't aware that such a need existed. When we published last year on a technology for analyzing sperm to detect male infertility, we were approached by those who had read about our work and were wondering if we could develop a smart-phone based system to provide ovulation testing at home," said corresponding author Hadi Shafiee, Ph.D., principal investigator at the BWH Division of Engineering in Medicine and Renal Division of Medicine. "Our study indicates that an accurate, automated and low-cost test is indeed possible."
 
Current methods for monitoring woman's fertility are often costly or subjective. These methods include ovulation detection through luteinizing hormone (LH) level determination (a clinical blood test or at-home urine "dip stick" test), rectal or basal body temperature analysis, cervical mucus characterization and salivary ferning analysis. Salivary ferning refers to the unique appearance of dried saliva from a woman who is ovulating—when collected on a glass slide, saliva takes on a crystallized structure that resembles fern leaves. While relatively inexpensive and simple, salivary fern analysis is highly subjective; when performed by the lay consumer, this approach is prone to misinterpretation.
 
To overcome this challenge, Shafiee and colleagues developed an automated process for detecting ferning in a saliva sample. The developed AI algorithm was pre-trained with 1.4 million ImageNet images and retrained with more than 1500 salivary ferning images to be able to classify saliva images into two categories: Ovulating and non-ovulating samples.
 
The team then evaluated the system's ability to differentiate ovulating and non-ovulating human saliva samples from six subjects. The women collected and tested their saliva samples using the cell phone system during both ovulating and non-ovulating phases of their menstrual cycle (results were confirmed using a urine test). To perform the test, saliva was collected on a microfluidic device, smeared, and left to air dry. The microfluidic device with the air-dried sample was then inserted into a 3D printed optical attachment affixed to a smartphone. The software then analyzed the fern patterns, correctly identifying ovulation in 99 percent of samples and non-ovulation in 100 percent of the samples.
 
"One of the biggest advantages to this method is cost—whereas the cost of non-reusable urine stick tests can add up to $210 to $240 over the course of six months, our device represents the possibility of a one-time purchase," said co-author Manoj Kumar Kanakasabapathy, a senior research assistant in the Shafiee laboratory. "Beyond human ovulation, there are applications here as well for animal breeding and even for dry eye disease, which can also produce fern-like patterns in samples from eye mucosa."
 
"One of the biggest problems with saliva-based tests, we realized, was that users find it difficult to interpret the fern patterns," said Prudhvi Thirumalaraju, another co-author of this study and a senior research assistant in Shafiee's laboratory. "We figured that advances in AI can be put to good use here, to help people get objective results on their smartphones."
 
The new system is constrained by some of the same limitations as traditional ovulation tests, and cannot detect ovulation in women with estrogen imbalance, cysts in the ovaries, and those who take fertility medications. Smoking or alcohol consumption may also interfere with accurate detection. The device will require additional testing in a larger population and approval by the Federal Drug Administration before it can be brought to market. 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