Discover the newest research about AI innovations in 👤 Personalized Medicine.
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.
Moving diagnostic tools directly into primary care clinics can bypass the systemic barriers that historically leave minority patients underserved.
A new reanalysis reveals that highly praised machine learning survival models underperform both human doctors and a thirty-year-old statistical formula at predicting patient death at critical clinical milestones.
