Medi Whale Co. signed a side agreement of ‘Dr. Noon’ demonstration agreement with Khanty-Mansiysk Hospital (Russia). Last December of 2017, Medi Whale have signed an agreement with Khanty-Mansiysk District for appliance of AI eye examination software based on deep learning artificial intelligence. The agreement of this December is a side agreement of the previous agreement,
Google displayed the AI technology which can predict individual patient’s medical treatment results by analyzing their electronic health record (EHR) through deep learning system. It was difficult to analyze EHR as several complicated data such as the quantity of patients, different type of diseases, prescriptions, and surgical operations are presented. Moreover, since some data is
Medi Whale and its product, Dr. Noon, was introduced to media by the Korea Economic Daily. The article is based on interview of Choi, the CEO of Medi Whale. Choi said that their program Dr. Noon can “diagnose disease risk of cardiovascular, macular, and optic nerve with 95% reliability by analyzing the fundus image”. The
Along with the study of evaluating diabetic retinopathy by applying deep learning to retinal fundus image, predicting cardiovascular risk factor also became focused in medical field. As identified retinal fundus images can display distinctive features of optic disc or blood vessels, correlation between heart diseases and retinal disease, it allowed to predict the cardiovascular risk
Medi Whale Co. introduced their research in EuroPCR, the biggest cardiology workshop in Paris. This annually holding workshop is mainly focused on invasive cardiac surgery. In this year, 10,987 professionals were participated and shared their individual field research. From this workshop, Medi-Whale represented the research result of AI which can assist physician’s diagnosis and evaluation
Before when deep learning was not displayed in ophthalmology, diabetic retinopathy was needed to be evaluated and prescribed through human effort. IDx-DR is using the algorithm which applied two development operating set (high specificity & high sensitivity) to identify diabetic retinopathy and to evaluate patient’s common status. Referable and non-referable diabetic retinopathies were evaluated by
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