Via Deborah Teramis Christian. <\/p>\n\n\n\n
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Originally shared by Kam-Yung Soh<\/strong><\/p>\n\n\n\n <\/p>\n\n\n\n Nice work.<\/strong> “When 16-year-old Kavya Kopparapu wasn\u2019t attending conferences, giving speeches, presiding over her school\u2019s bioinformatics society, organizing a research symposium, playing piano, and running a non-profit, she worried about what to do with all her free time.<\/p>\n\n\n\n […]<\/p>\n\n\n\n Of 415 million diabetics worldwide, one-third will develop retinopathy. Fifty percent will be undiagnosed. Of patients with severe forms, half will go blind in five years. Most will be poor.<\/p>\n\n\n\n <\/p>\n\n\n\n \u201cThe lack of diagnosis is the biggest challenge,\u201d Kopparapu says. \u201cIn India, there are programs that send doctors into villages and slums, but there are a lot of patients and only so many ophthalmologists.\u201d What if there were a cheap, easy way for local clinicians to find new cases and refer them to a hospital?<\/p>\n\n\n\n <\/p>\n\n\n\n That was the genesis of Eyeagnosis, a smartphone app plus 3D-printed lens that seeks to change the diagnostic procedure from a 2-hour exam requiring a multi-thousand-dollar retinal imager to a quick photo snap with a phone.<\/p>\n\n\n\n <\/p>\n\n\n\n Kopparapu and her team\u2014including her 15-year-old brother, Neeyanth, and her high school classmate Justin Zhang\u2014trained an artificial intelligence system to recognize signs of diabetic retinopathy in photos of eyes and offer a preliminary diagnosis. She presented the system at the O\u2019Reilly Artificial Intelligence conference, in New York City, last month.<\/p>\n\n\n\n <\/p>\n\n\n\n \u201cThe device is ideal for making screening much more efficient and available to a broader population,\u201d says J. Fielding Hejtmancik, an expert in visual diseases at the National Institutes of Health (NIH). Other research groups, including Google and Peek Vision, have recently announced similar systems, but Hejtmancik is impressed with the students\u2019 ingenuity. \u201cThese kids have put things together in a very nice way that\u2019s a bit cheaper and simpler than most [systems designed by researchers]\u2014who, by the way, all have advanced degrees!\u201d<\/p>\n\n\n\n […]<\/p>\n\n\n\n Hejtmancik, the NIH expert, notes that there\u2019s a long road to clinical adoption. \u201cWhat she\u2019s going to need is a lot of clinical data showing that [Eyeagnosis] is reliable under a variety of situations: in eye hospitals, in the countryside, in clinics out in the boonies of India,\u201d he says.<\/p>\n\n\n\n <\/p>\n\n\n\n Still, Hejtmancik thinks the system has real commercial potential. The only problem, he says, is that it\u2019s so cheap that big companies might not see the potential for a profit margin. But that affordability \u201cis exactly what you want in medical care, in my opinion,\u201d he says.”<\/p>\n\n\n\n <\/p>\n\n\n\n Harish Pillay Jyoti Q Dahiya<\/p>\n\n\n\n