Discover the newest research about AI innovations in 👤 Personalized Medicine.
A new benchmark shows that expensive tabular foundation models offer almost no performance advantage over classic machine learning for predicting patient outcomes.
An AI model that calculates biological age from a simple eye photo could shift systemic disease screening from specialized clinics to the optometrist’s chair.
A new AI system called MedGenesis can compress years of clinical research into hours by autonomously generating hypotheses and analyzing patient data.
A new AI model predicts immunotherapy success across different cancers by translating complex genetic data into clear biological concepts.
A newly validated artificial intelligence model is challenging the expensive, slow-moving monopoly of genomic sequencing in breast cancer care.
A new AI tool bypasses the limits of scarce patient data to identify a two-protein signature that accurately flags a deadly, non-HPV cervical cancer.
A new language model attempts to solve a major diagnostic bias by separating normal hormonal transitions from actual viral damage in women.
A new machine learning model proves that tracking silent organ damage is far more predictive of survival than standard blood pressure readings.
A newly cleared neuromodulation system shifts PTSD treatment from trial-and-error pharmacology to personalized brain mapping.
An algorithm that spots diabetes risk a decade early could solve a massive bottleneck in preventive healthcare—if health systems actually know how to act on the data.
