2018年世界人工智能大會上，微軟全球執行副總裁、微軟人工智能及微軟研究事業部負責人沈向洋博士公布了Airdoc和微軟和禮來的合作，于此同時微軟總部對Airdoc進行了詳盡的專訪，采訪內容如下：

　　對很多人來說，人工智能已經可以為我們的健康做出巨大貢獻，現在人工智能（AI）只需不到一秒鐘就可以識別你的視網膜，找到潛在的慢性疾病。

　　Airdoc是一家中國快速發展并且擁有全球使命的創業公司，Airdoc研發了可以從視網膜影像中識別數十種慢性疾病和并發癥的病變的人工智能慢性病識別算法：可以識別從糖尿病到心血管疾病再到視神經疾病等慢性疾病。

　　現在的人工智能可以在瞬間識別慢性疾病

　　（Airdoc創始人張大磊）

　　該算法在視網膜病變識別準確率已經和頂級醫生診斷水平相當。并且在整個操作過程中擁有無痛、低成本和自動化等眾多特點，它可以在全世界范圍內為大人群提供健康服務。

　　“我們將算法布到云端，從而幫助用戶更好的了解自己的健康情況。”在家人發生醫療問題后，為了讓更多的患者能夠享受更好的醫療服務，張大磊在四年前創立了Airdoc。

　　長期以來，視網膜檢查一直都是醫生工作中的常規檢查，通過視網膜不僅能夠檢測眼睛的健康狀況，還能夠檢查身體其他部位的情況。為了更好的讓人工智能識別視網膜影像，張大磊組建了一支志同道合的團隊，在Microsoft Azure的幫助下，訓練人工智能尋找微小的疾病跡象，如斑點、出血、變色、血管變形和其他異常，最終研發出了Airdoc慢性病識別算法。

　　“我們發現微軟的云基礎設施可以幫我們更好的對算法進行訓練，”張大磊說， “在Azure中訓練深度學習模型非常容易。同時Azure的數據的安全性十分有保障，這在我們日常的工作中至關重要。Airdoc一直與微軟機器學習團隊密切合作?！?/p>

　　張大磊在五道口的辦公室里展示了Airdoc的慢性病識別系統產品。

　　只需要坐在凳子上，將下巴放在眼底照相機的支架上，凝視眼前的黑暗。然后眼前會出現一個綠色十字，片刻之后，有一道白光閃現就完成了視網膜影像的拍攝，然后另外一只眼鏡重復這個過程。

　　機器拍攝了高分辨率的視網膜影像后，算法立即將視網膜影像發送到云端，在云端只需要20到30毫秒（大約與眨眼相同的時間）就可以完成視網膜影像的識別。

　　現在的人工智能可以在瞬間識別慢性疾病

　　（Airdoc產品體驗）

　　片刻之后，一個描述詳細的診斷儀表板將發送到您的微信上?？梢耘袛嗦圆牡偷街械鹊礁叩娘L險程度。如果有問題，它會敦促您尋求專業的醫療幫助。

　　現在Airdoc慢性病識別算法可以直接識別30種疾病和并發癥，未來這個數字將會被提高到50，最終可能超過200。

　　張大磊認為Airdoc的算法在醫療供給端提供了新的服務，人工智能可以大規模提供技術支持從而緩解醫療資源不足的情況。到目前為止，Airdoc已經完成超過112萬人次的篩查，遍布中國、美國、印度、英國和非洲部分地區。 “Airdoc用戶遍布全球，希望我們的慢性病識別產品可以幫助用戶更好的預防各種慢性疾病?！?/p>

　　中國擁有13億人口，有超過1.14億人患有糖尿病 ， 但是糖尿病的知曉率只有30%，另外70%的人不知道自己已經患病，如果沒有及早發現，最終會患有嚴重的并發癥，比如失明、中風和其他可能致命的疾病。

　　“糖尿病性視網膜病變（DR）是糖尿病最常見和嚴重的并發癥之一。一旦患者出現癥狀，他們已經處于DR的晚期，在沒有及時治療的情況下會失明，“上海長征醫院眼科主任魏銳利教授表示， Airdoc的產品已經在上海長征醫院展開應用，為醫生提供準確，簡單的診斷工具。

　　現在的人工智能可以在瞬間識別慢性疾病

　　（上海長征醫院使用Airdoc產品）

　　“通過人工智能可以進行初步檢查，醫生可以對患者進行更好的安排， 醫生有更多時間處理相對嚴重的病例。”張大磊說。

　　在中國可以自主識別視網膜圖像的眼科醫生數量遠遠不足，Airdoc正在積極尋找人工智能的使用場景。 今年Airdoc將會在中國最大的眼鏡零售連鎖眼鏡店中的200家門店中安裝Airdoc的慢性病識別系統，未來1年內將會遍布1200家眼鏡店，這樣當顧客進行眼科檢查或購買眼鏡時，可以快速進行視網膜掃描完成健康的檢查。

　　于此同時，Airdoc正在研發一種新型的設備，可以幫助用戶進行持續監測，類似VR眼鏡的一個設備，可以實時監控我們的慢性病的變化情況。

　　英文原文：

　　Diagnosing diseases with AI in the blink of an eye

　　Let artificial intelligence （AI） look into your eyes. In less than a second it can check for potential medical problems and it might just save your life.

　　Airdoc， a fast-growing start-up in China with a global mission， has created an AI-driven system that takes and analyses photographic images of the retina at the back of each eyeball. From this data， it seeks out the telltale signs of dozens of chronic illnesses and conditions such as diabetes， hypertension， arteriosclerosis， optic nerve disease， high myopia， age-related macular degeneration， and many more.

　　Painless， low-cost， and automated， it has a higher accuracy rate on finding indications of diseases on retinal images than slower conventional diagnoses by doctors. As such， it has the potential to make preventative healthcare available to millions of people， not just in China， but around the world.

　　“We are using an algorithm in the cloud to save the lives of people who don’t even know they have serious medical problems，” says Ray Zhang， who founded Airdoc four years ago.

　　Doctors have long examined the retina not just to gauge the health of the eye， but also for signs about the rest of the div. Knowing this， Ray put together a team of like-minded IT engineers who amassed data from the pixels of thousands of retinal scans and created an algorithm. With the power of Microsoft Azure’s machine learning capabilities， they set about teaching it how to look for tiny signs of disease like specks， spots， discoloration， deformed blood vessels， and other abnormalities.

　　“We found that Microsoft has the most advanced cloud infrastructure to do this，” Zhang said. “We have been working with the Microsoft machine learning team very closely. Training deep learning models in Azure is very easy.” Patient data is also kept secure and confidential by Azure， which is “mission-critical to our service level for our customers.”

　　In his office in suburban Beijing， Zhang proudly demonstrated the physical part of Airdoc’s system – a small desktop device that looks similar to a scanner a neighborhood optometrist might use for a routine eye exam.

　　You sit on a stool， lean forward， place your chin on a padded brace， and stare into the darkness of an eyepiece. The algorithm then takes over， precisely adjusting the angle of your head until a green cross comes into focus in the gaze of your right eye. A moment later there’s a bright， but not uncomfortable， flash of white light. The process is repeated for your left eye.

　　The machine has just taken high-resolution medical-grade images of both your retinas. It instantly sends them to the cloud where it takes 20 to 30 milliseconds （about the same time as an eye blink） of computation to analyze both.

　　Moments later an impressively detailed diagnostic dashboard is sent to your smartphone. It rates from low to medium to high your susceptibility to a long list of diseases. If there is a problem， it urges you to seek professional medical help.

　　Right now， it can search for 30 diseases. More machine learning will soon boost that number to 50， and eventually， it could go beyond 200.

　　Zhang regards his system as a gamechanger because of its potential to deliver at scale and relieve stretched medical resources. To date， it has scanned more than 1.12 million people， mostly in China， but also in the United States， India， Britain， and parts of Africa. “Airdoc users are all over the world. We hope our deep learning technology can prevent all kinds of disease.”

　　China， with a population of 1.3 billion， only has about 1，100 eye doctors who are qualified to analyze retinal images. So， the challenge of providing adequate diagnostic services is truly massive – and perhaps no more so than for the epidemic of diabetes.

　　Authorities estimate as many as 114 million Chinese have diabetes – but only 30 percent of them know that. The other 70 percent are unaware and， without early detection， will eventually be struck down with serious maladies， like blindness， strokes and other potentially fatal conditions.

　　“Diabetic retinopathy， or DR， is one of the most common and serious complications of diabetes. Once patients feel symptoms， they are already in a severe stage of DR and will go blind without proper treatment，” says Dr. Rui Li Wei （pictured in top image） of Shanghai’s Changzheng Hospital， one of several major medical institutions that now routinely uses Airdoc’s technology as a quick， accurate， and simple diagnostic tool.

　　By taking on the time consuming and laborious task of reading scans， physicians can more easily identify and prioritize patients with serious problems. “It frees up a doctor’s time to work with more severe cases，” Zhang says.

　　Meanwhile， Airdoc is looking at new ways to widen its reach. A major Chinese optical retail chain has recently installed its machines in 200 stores so that when customers come in for an eye check or to buy glasses， they can also get a quick retinal scan. They hope to increase this to 1200 stores within the next three years.

　　Airdoc is also exploring how it can give ongoing help to patients with diabetes and other diseases. It is currently developing a visor – like those used for virtual reality games – that could regularly conduct scans and let their doctors see how their treatment is progressing.