2018年世界人工智能大會上,微軟全球執(zhí)行副總裁、微軟人工智能及微軟研究事業(yè)部負(fù)責(zé)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(jìn)行了詳盡的專訪,采訪內(nèi)容如下:
對很多人來說,人工智能已經(jīng)可以為我們的健康做出巨大貢獻(xiàn),現(xiàn)在人工智能(AI)只需不到一秒鐘就可以識別你的視網(wǎng)膜,找到潛在的慢性疾病。
Airdoc是一家中國快速發(fā)展并且擁有全球使命的創(chuàng)業(yè)公司,Airdoc研發(fā)了可以從視網(wǎng)膜影像中識別數(shù)十種慢性疾病和并發(fā)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(jīng)疾病等慢性疾病。
(Airdoc創(chuàng)始人張大磊)
該算法在視網(wǎng)膜病變識別準(zhǔn)確率已經(jīng)和頂級醫(yī)生診斷水平相當(dāng)。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(nèi)為大人群提供健康服務(wù)。
“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(fā)生醫(yī)療問題后,為了讓更多的患者能夠享受更好的醫(yī)療服務(wù),張大磊在四年前創(chuàng)立了Airdoc。
長期以來,視網(wǎng)膜檢查一直都是醫(yī)生工作中的常規(guī)檢查,通過視網(wǎng)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(wǎng)膜影像,張大磊組建了一支志同道合的團(tuán)隊,在Microsoft Azure的幫助下,訓(xùn)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(fā)出了Airdoc慢性病識別算法。
“我們發(fā)現(xiàn)微軟的云基礎(chǔ)設(shè)施可以幫我們更好的對算法進(jìn)行訓(xùn)練,”張大磊說, “在Azure中訓(xùn)練深度學(xué)習(xí)模型非常容易。同時Azure的數(shù)據(jù)的安全性十分有保障,這在我們?nèi)粘5墓ぷ髦兄陵P(guān)重要。Airdoc一直與微軟機(jī)器學(xué)習(xí)團(tuán)隊密切合作。”
張大磊在五道口的辦公室里展示了Airdoc的慢性病識別系統(tǒng)產(chǎn)品。
只需要坐在凳子上,將下巴放在眼底照相機(jī)的支架上,凝視眼前的黑暗。然后眼前會出現(xiàn)一個綠色十字,片刻之后,有一道白光閃現(xiàn)就完成了視網(wǎng)膜影像的拍攝,然后另外一只眼鏡重復(fù)這個過程。
機(jī)器拍攝了高分辨率的視網(wǎng)膜影像后,算法立即將視網(wǎng)膜影像發(fā)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(wǎng)膜影像的識別。
(Airdoc產(chǎn)品體驗)
片刻之后,一個描述詳細(xì)的診斷儀表板將發(fā)送到您的微信上??梢耘袛嗦圆牡偷街械鹊礁叩娘L(fēng)險程度。如果有問題,它會敦促您尋求專業(yè)的醫(yī)療幫助。
現(xiàn)在Airdoc慢性病識別算法可以直接識別30種疾病和并發(fā)癥,未來這個數(shù)字將會被提高到50,最終可能超過200。
張大磊認(rèn)為Airdoc的算法在醫(yī)療供給端提供了新的服務(wù),人工智能可以大規(guī)模提供技術(shù)支持從而緩解醫(yī)療資源不足的情況。到目前為止,Airdoc已經(jīng)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(qū)。 “Airdoc用戶遍布全球,希望我們的慢性病識別產(chǎn)品可以幫助用戶更好的預(yù)防各種慢性疾病。“
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(jīng)患病,如果沒有及早發(fā)現(xiàn),最終會患有嚴(yán)重的并發(fā)癥,比如失明、中風(fēng)和其他可能致命的疾病。
“糖尿病性視網(wǎng)膜病變(DR)是糖尿病最常見和嚴(yán)重的并發(fā)癥之一。一旦患者出現(xiàn)癥狀,他們已經(jīng)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(yī)院眼科主任魏銳利教授表示, Airdoc的產(chǎn)品已經(jīng)在上海長征醫(yī)院展開應(yīng)用,為醫(yī)生提供準(zhǔn)確,簡單的診斷工具。
(上海長征醫(yī)院使用Airdoc產(chǎn)品)
“通過人工智能可以進(jìn)行初步檢查,醫(yī)生可以對患者進(jìn)行更好的安排, 醫(yī)生有更多時間處理相對嚴(yán)重的病例。”張大磊說。
在中國可以自主識別視網(wǎng)膜圖像的眼科醫(yī)生數(shù)量遠(yuǎn)遠(yuǎn)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(tǒng),未來1年內(nèi)將會遍布1200家眼鏡店,這樣當(dāng)顧客進(jìn)行眼科檢查或購買眼鏡時,可以快速進(jìn)行視網(wǎng)膜掃描完成健康的檢查。
于此同時,Airdoc正在研發(fā)一種新型的設(shè)備,可以幫助用戶進(jìn)行持續(xù)監(jiān)測,類似VR眼鏡的一個設(shè)備,可以實時監(jiān)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 body. 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.
- 蜜度索驥:以跨模態(tài)檢索技術(shù)助力“企宣”向上生長
- 為什么年輕人不愛換手機(jī)了
- 柔宇科技未履行金額近億元被曝已6個月發(fā)不出工資
- 柔宇科技被曝已6個月發(fā)不出工資 公司回應(yīng)欠薪有補(bǔ)償方案
- 第六座“綠動未來”環(huán)保公益圖書館落地貴州山區(qū)小學(xué)
- 窺見“新紀(jì)元”,2021元宇宙產(chǎn)業(yè)發(fā)展高峰論壇“廣州啟幕”
- 以人為本,景悅科技解讀智慧城市發(fā)展新理念
- 紐迪瑞科技/NDT賦能黑鯊4 Pro游戲手機(jī)打造全新一代屏幕壓感
- 清潔家電新老玩家市場定位清晰,攜手共進(jìn),核心技術(shù)決定未來
- 新思科技與芯耀輝在IP產(chǎn)品領(lǐng)域達(dá)成戰(zhàn)略合作伙伴關(guān)系
- 芯耀輝加速全球化部署,任命原Intel高管出任全球總裁
免責(zé)聲明:本網(wǎng)站內(nèi)容主要來自原創(chuàng)、合作伙伴供稿和第三方自媒體作者投稿,凡在本網(wǎng)站出現(xiàn)的信息,均僅供參考。本網(wǎng)站將盡力確保所提供信息的準(zhǔn)確性及可靠性,但不保證有關(guān)資料的準(zhǔn)確性及可靠性,讀者在使用前請進(jìn)一步核實,并對任何自主決定的行為負(fù)責(zé)。本網(wǎng)站對有關(guān)資料所引致的錯誤、不確或遺漏,概不負(fù)任何法律責(zé)任。任何單位或個人認(rèn)為本網(wǎng)站中的網(wǎng)頁或鏈接內(nèi)容可能涉嫌侵犯其知識產(chǎn)權(quán)或存在不實內(nèi)容時,應(yīng)及時向本網(wǎng)站提出書面權(quán)利通知或不實情況說明,并提供身份證明、權(quán)屬證明及詳細(xì)侵權(quán)或不實情況證明。本網(wǎng)站在收到上述法律文件后,將會依法盡快聯(lián)系相關(guān)文章源頭核實,溝通刪除相關(guān)內(nèi)容或斷開相關(guān)鏈接。