Discover the newest research about AI innovations in 👤 Personalized Medicine.
Measuring a single protein has been the gold standard for tracking ALS, but a new multi-protein signature suggests we have been missing the bigger biological picture.
A new multi-center model uses basic clinical data to flag brain metastasis before symptoms appear, challenging the need for expensive, complex biomarkers.
A new machine learning model proves we do not need expensive imaging or complex protein tracking to find patients whose knee pain will soon spike.
A new nine-protein blood signature outperforms traditional clinical models and single-marker tests in predicting how fast ALS progresses.
A new commercial retinal implant challenges the boundary between biological sight and digital translation, forcing healthcare to rethink how we treat blindness.
A massive consolidation in cancer diagnostics reveals the steep financial price of dominating the liquid biopsy market.
A new study shows AI-generated synthetic patients can replicate cancer trial results, potentially shrinking the need for human control groups.
A new deep learning tool bypasses the need for massive non-European genetic trials by adapting existing risk models to diverse populations.
Averaging tumor data has long blinded oncologists to the specific, high-risk cells that drive patient mortality.
A new machine learning model uses simple blood and nutrition markers to predict which uterine cancer patients can safely skip aggressive surgery to preserve their fertility.
