AI tools are moving from research into consumer products. Below: what the published research describes about current capabilities and limitations.
A measured guide to reading your own wearable data over time: which metrics are robust, which are noisy, how to spot trends and when a reading warrants a doctor.
12 min read · 2026-06-04 AI toolsA measured guide to consumer AI health apps in 2026: the main categories, what the evidence and regulators actually say, and how to evaluate any one of them.
12 min read · 2026-06-04 PersonalisationA measured look at personalised health optimisation: where evidence supports tailoring advice to the individual, where claims run ahead of the data, and what to do now.
12 min read · 2026-06-04 AI in HealthConsumer health AI spans symptom checkers, image recognition, conversational agents, wearable interpretation, and document scanners. This page describes what validation studies have measured across categories.
11 min read · 2026-06-01 AI regulationMore than 950 AI-enabled medical devices have FDA clearance, mostly in radiology. This page describes the clearance pathways, what clearance guarantees, and how to read the difference between regulated AI and wellness apps.
11 min read · 2026-06-01 AI validationValidation studies have measured how accurately AI symptom checkers diagnose and triage. The best tools achieve ~70% top-3 diagnostic accuracy; all over-recommend care. This page summarises what the research describes.
11 min read · 2026-06-01 AI validationMedical imaging is the strongest category of validated medical AI. This page describes what research has measured across diabetic retinopathy, skin cancer, stroke triage, mammography, and chest X-ray.
11 min read · 2026-06-01