[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-a-retinal-ai-model-that-learns-from-scans-it-never-sees":10,"sections":40},{"siteName":4,"siteTagline":5,"publisherName":4,"contactEmail":6},"The Revision","Tech news, decoded.","editor@therevision.news",{"gaMeasurementId":8,"adsenseClientId":9},"G-ZW2MV82GYR","ca-pub-8533917693782264",{"article":11},{"id":12,"slug":13,"title":14,"dek":15,"body_md":16,"tags_json":17,"published_at":18,"created_at":19,"updated_at":20,"status":21,"review_note":22,"review_notes":23,"image_url":22,"persona_id":22,"persona_name":22,"section":30,"tags":31,"sources":35,"feedback":39,"feedback_at":22,"cost_usd":39,"total_tokens":39},2974,"a-retinal-ai-model-that-learns-from-scans-it-never-sees","A Retinal AI Model That Learns From Scans It Never Sees","EyeMVP was trained on paired eye scans from 112,642 patients to make standard fundus photos smarter — without needing the expensive scan at diagnosis.","A new AI model for retinal screening extracts depth information from cheap eye photos — without actually taking a depth scan.\n\nResearchers trained EyeMVP on nearly 675,000 paired image sets, each pairing a standard color fundus photo with an optical coherence tomography scan from the same eye on the same day, drawn from 112,642 patients across eight hospitals. The idea: during training, the model learns what an OCT scan would reveal, so that at diagnosis time it can work from the fundus photo alone. OCT provides the kind of cross-sectional, depth-resolved detail that fundus photography cannot, but OCT equipment is expensive and far less common in mass screening programs. EyeMVP sidesteps that access gap by baking OCT knowledge into a model that only needs the cheaper image at inference.\n\nThe clinical stakes are real: the model hit AUROCs of 0.923 for macular edema and 0.867 for myopic macular schisis, two conditions that are notoriously hard to catch in standard fundus photos. In a reader study, EyeMVP outperformed junior and intermediate ophthalmologists on macular edema — though not senior specialists — and surpassed all human groups on myopic macular schisis. That gap matters for healthcare systems where senior ophthalmologists are the scarce resource.\n\nThe honest caveat is that this is a preprint, not a peer-reviewed clinical deployment, and reader studies are a controlled setting — not a busy screening clinic. Still, the approach of offloading expensive modality knowledge into a cheaper-to-run model at inference is a legitimate architectural direction, one that has parallels in radiology AI where MRI-informed CT models have drawn similar interest.","[\"ai\",\"medical-imaging\",\"ophthalmology\",\"research\"]","2026-06-30T04:00:00.000Z","2026-06-30T16:14:21.406Z","2026-06-30T16:14:24.105Z","published",null,[24],{"id":25,"reviewer":26,"round":27,"reason":28,"status":29},"editor-r1","editor",1,"The reader study finding is misstated: the draft says EyeMVP 'beat junior and intermediate ophthalmologists on macular edema and outperformed all human groups on myopic macular schisis,' omitting that it did NOT surpass senior ophthalmologists on macular edema — a material qualification present in the source that must be reflected accurately.","resolved","ai",[30,32,33,34],"medical-imaging","ophthalmology","research",[36],{"name":37,"url":38},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2606.15129",0,{"sections":41},[42,46,51,56,61,66,71,76,81,86,91,95,100,105],{"name":43,"slug":30,"count":44,"latest_published_at":45},"AI",2590,"2026-07-16T04:00:00.000Z",{"name":47,"slug":48,"count":49,"latest_published_at":50},"Security","security",294,"2026-07-15T19:59:48.000Z",{"name":52,"slug":53,"count":54,"latest_published_at":55},"Deals","deals",179,"2026-06-29T20:02:07.000Z",{"name":57,"slug":58,"count":59,"latest_published_at":60},"Policy","policy",158,"2026-07-16T00:02:48.000Z",{"name":62,"slug":63,"count":64,"latest_published_at":65},"Hardware","hardware",122,"2026-07-14T19:46:26.000Z",{"name":67,"slug":68,"count":69,"latest_published_at":70},"Consumer Tech","consumer-tech",93,"2026-07-13T13:20:48.000Z",{"name":72,"slug":73,"count":74,"latest_published_at":75},"Software","software",70,"2026-07-13T19:52:25.000Z",{"name":77,"slug":78,"count":79,"latest_published_at":80},"Science","science",66,"2026-07-10T10:29:37.000Z",{"name":82,"slug":83,"count":84,"latest_published_at":85},"Dev Tools","dev-tools",59,"2026-07-07T04:00:00.000Z",{"name":87,"slug":88,"count":89,"latest_published_at":90},"Gaming","gaming",41,"2026-07-09T04:00:00.000Z",{"name":92,"slug":93,"count":89,"latest_published_at":94},"Startups","startups","2026-06-29T20:55:50.000Z",{"name":96,"slug":97,"count":98,"latest_published_at":99},"General","general",29,"2026-07-10T22:28:58.000Z",{"name":101,"slug":102,"count":103,"latest_published_at":104},"Reviews","reviews",20,"2026-06-24T12:00:01.000Z",{"name":106,"slug":107,"count":108,"latest_published_at":109},"How-To","how-to",6,"2026-06-16T09:00:00.000Z"]