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Infervision’s deep learning medical imaging platform acts as second pair of eyes to identify multiple diseases.
January 14, 2019
By: Infervision
Infervision, a tech company using big data and artificial intelligence (AI) to assist and improve medical diagnoses, has launched InferRead CT Chest, a new product concept that detects four different conditions with just one set of chest scans, leading to faster and more comprehensive medical diagnoses. Additionally, Infervision is also introducing a new product concept for fast diagnosis in emergency conditions. The new InferRead CT Chest will allow a doctor to review an image only once to perform multiple disease screenings in the chest including: lung nodule screening; chest fractures, bone metastases and bone tumor screenings; chronic lung disease (such as emphysema) screening; and cardiac calcification screening. The lung nodule screening, while a core Infervision product, has been enhanced over the past year so it can now provide a complete view of the nodule, including volume and density. This product can automatically compare similar cases from a case report bank to provide further information and diagnostic information to physicians. Also being introduced by Infervision is a new product concept which aims to help manage emergency conditions including stroke and bone fractures, allowing doctors to use AI for fast diagnosis and treatment decisions. With this concept, the company is using the power of AI to improve emergency room workflow and it is now being tested and continually improved in several hospitals in China. Currently China-based Infervision works with 250 of the top hospitals globally including top-rated facilities in the United States, Japan, Germany, and Spain. In China, 70 percent of first-tier hospitals use the company’s InferRead CT Lung solution. Since the launch of the solution in 2017 it has helped radiologists screen more than 20,000 lung cancer reports each day. By using the platform radiologists can quickly read the thousands of images available for each patient and bring to the doctor’s attention only those scans that need a more thorough review. “At the end of the day, our goal is improving a person’s life. We simply want to use our technology to act as an aide and help doctors perform at the highest level. Doctors are already working long hours with many cases to manage. Now, we can provide more comprehensive all-in-one reports which will streamline radiologist workflow, and which may be life saving for many patients,” said Infervision founder and CEO Chen Kuan. Used to reduce the highly-repetitive work radiologists do each day, the goal of Infervision is to help doctors deliver more accurate reports faster. In fact, when Infervision’s technology and a group of radiologists recently went head-to-head in a report-reading experiment with different types and sizes of nodules. Infervision’s AI-CT predicted more accurately than radiologists in every category. “Infervision believes that technology plays an important role in AI development, but technology is not the only requirement for developing excellent products. Clinical workflow integration, robustness of the AI model, as well as scalability are all important elements to succeed,” continued Kuan. “Infervision’s R&D team will work closely with the radiologists and physicians from various medical institutions around the world to understand their needs and challenges with regard to AI solutions so we can continually improve and develop the best-in-class AI solutions.” Infervision specializes in applying deep learning technology to medical image analysis. By utilizing massive medical data, Infervision creates clinically-valuable products and facilitates radiologists to make faster and more accurate diagnoses. Currently Infervision is collaborating with more than 250 hospitals. Infervision closed a $47 million Series B funding from Xianghe Capital, Sequoia Capital China, Qiming Venture Partners, and Genesis Capital. The Infervision founders and scientists studied at top universities and research institutions around the world.
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