
AI predicts liver cancer treatments using medical notes
A new AI model proves that the messy, unformatted text in patient charts is actually the most valuable tool for choosing liver cancer therapies.
Discover the newest research about AI innovations in 🎗 Oncology.

A new AI model proves that the messy, unformatted text in patient charts is actually the most valuable tool for choosing liver cancer therapies.

A new machine-learning model spots lung cancer from a simple urine sample, challenging the current reliance on costly scans and invasive blood draws.

Unsupervised machine learning reveals that tumor shape, not just invasion depth, dictates whether early colorectal cancer will return after endoscopic removal.

A new machine learning model can pinpoint the origin of mysterious cancers from simple blood fragments, shifting the focus of liquid biopsies from detection to direction.

A new study shows that AI foundation models can standardize cervical cancer screening across different countries, outperforming human pathologists where they struggle most.

A new deep learning model attempts to spot hard-to-find HER2-low breast cancers from standard tissue slides, but its modest accuracy reveals just how difficult this diagnostic boundary is to draw.

Elite cancer centers are finally trading exclusive data for global scale, shifting the balance of power in precision medicine.

A new partnership aims to bring precision medicine to a disease long starved of reliable biomarkers.

A new artificial intelligence model outperforms existing tools in spotting tiny cancer deposits in lymph nodes across multiple cancer types.

A new AI system can predict lymphoma subtypes and order diagnostic tests directly from initial biopsy scans, cutting down the days patients spend waiting for a diagnosis.