
When Telehealth Scale Collides With Patient Safety
The rush to digitize GLP-1 prescribing is exposing a dangerous rift between venture-backed growth targets and basic clinical caution.
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The rush to digitize GLP-1 prescribing is exposing a dangerous rift between venture-backed growth targets and basic clinical caution.

A new benchmark reveals that how we format electronic health records for large language models completely alters their clinical accuracy.

A massive consolidation in cancer diagnostics reveals the steep financial price of dominating the liquid biopsy market.

Deep learning models trained to spot Alzheimer’s disease are systematically blind to atypical forms of brain decay, raising doubts about their readiness for real-world clinics.

The battle for AI supremacy has moved from chatbots to wet labs, and Anthropic is spending heavily to challenge Google’s dominance in drug discovery.

Hospitals waste millions of blood culture tests on low-risk patients while missing critical infections, but a new machine learning model shows we can find more cases without running a single extra test.

Drug discovery is no longer just a biology problem; it is a massive infrastructure war.

A new clinical trial shows that AI can guide untrained operators to perform deep vein thrombosis scans, but the real value lies in filtering the patient queue rather than replacing human specialists.

A new regulatory fast-track aims to end the endless cycle of localized pilot programs that keep medical technology from reaching patients.

A new study shows that even advanced vision models struggle to predict preterm birth when tested on new hospital equipment.