Analysis
Original findings, recomputed and cross-checked.
Each analysis assembles something no single study or press release contains — a cross-study table, a recomputed rate — from the primary sources. To guard against a coding error rather than a typo, every finding is built independently by two different AI models and reconciled against the source, with the disagreements published. The data lives in the page for you to check and reuse.
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The AI eye exam can read the retina. Can it save sight?
Retinal AI can identify referable diabetic retinopathy quickly and accurately. Ground Truth traced 29 studies and 15 public claims through the care chain. Across 17 selected patient-count pathways, referral gains depended on the surrounding workflow; only two separately counted who needed treatment, and none reported completed treatment or a longitudinal vision-outcome denominator.
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Health records, then AI: ask what actually moved
Almost every health-technology claim rests on something that moved, and the trick is knowing what. Across twenty years of electronic medical records and now clinical AI in African health systems, the answer is consistent: documentation and process measures move; patient outcomes usually do not. The first registered randomized trial of an LLM assistant in African primary care improved the notes while leaving the 14-day patient outcome unchanged, and its documentation gains appeared only after human coaching was added. This review sets out every hard-outcome study we could find, and the five questions that separate a record improving from a patient improving.
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The scoreboard that can’t be drawn: what 15 “AI-beats-clinician” health studies actually measured
Fifteen studies say AI matches or beats clinicians in global health. Grouped honestly, “beats doctors” fractures into five different claims — no fair test, a win over the weakest human, a true tie with experts, an outright loss, and AI merely assisting a clinician — on a dozen scales that don’t compare, and almost never measured on a patient. An original, cross-checked dataset.