On May 10th, the Airdoc DR system was unveiled at the Microsoft Build2017 Developer Conference. DR is an auxiliary analysis system for diabetic retinopathy, which is used to identify and screen for sugar net lesions. Airdoc artificial intelligence-assisted analysis program has been popularized in many hospitals including Shanghai Changzheng Hospital, becoming a doctor to quickly and accurately analyze diseases. A good helper.
With its artificial intelligence-assisted analysis application in the medical field, Airdoc became the first Chinese startup to appear on the Keynote at the Build Conference. It is also a key case for Microsoft to screen from the artificial intelligence companies in more than 140 countries around the world.
The Build Developers Conference is Microsoft's annual event. In the past, developers from tens of millions of people around the world have paid close attention in various ways. More than 2,000 US dollars in on-site tickets are hard to find. The Chinese company that debuted this time is Airdoc, an artificial intelligence company in the medical field that has always been low-key.
It is understood that Airdoc has already carried out in-depth cooperation with dozens of top medical institutions in China and the United States. It is also the first artificial intelligence enterprise in the medical field in China that has received multiple rounds of investment from well-known institutions.
(Photo: Airdoc debut at Microsoft Build 2017 conference)
Sugar net fundus image recognition and sugar net lesion area detection
Diabetic retinal fundus lesions (sugar net) is one of the most common complications of diabetes. The number of diabetic patients in China has increased year by year, and has exceeded 100 million people, of which sugar net patients account for 25%-38% of diabetic patients. According to the World Health Organization, by 2030, the number of global sugar net patients will increase to 366 million.
Sugar nets are irreversible blinding eye diseases. Early patients with sugar nets are usually asymptomatic, and most of them are in a heavier stage. Early diagnosis and treatment of patients with sugar nets can effectively prevent visual loss and blindness.
Based on the fundus data marked by a large number of experts, Airdoc uses deep learning techniques to design a specific deep neural network structure to realize fundus fundus image recognition and sugar net lesion detection.
Professor Wei Ruili from Shanghai Changzheng Hospital commented on Airdoc: "With the Airdoc DR system, we can extend the hands of our professional doctors and our inspection technology to all parts of the country, that is to say, in any corner, mobile phone shooting, professional instrument shooting The images can be transmitted to the cloud for assisted analysis to obtain accurate recommendations so that patients can get early prevention and analysis recommendations at any time."
Professor Wei Ruili, Shanghai Changzheng Hospital, Second Military Medical University
Dr. Huang Wei from Shanghai Changzheng Hospital said in an interview that Airdoc DR is very easy to use and easy to use. “Airdoc DR is very useful and easy to use. We can access it directly from the cloud in the hospital. Log in to the system and enter some medical history. Information, upload photos, the system will automatically give a supplementary reference."
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