An artificial intelligence (AI) model developed by researchers at The University of Texas MD Anderson Cancer Center ...

Two complementary predictors (DAAE-M and ELIE) estimate individualized 5-year progression risk using routine clinical data, ...

A new review in Science China Life Sciences examines how machine learning and host-microbiome multi-omics can be combined to better understand health and disease. The article outlines the road from ...

Findings support model in which accelerated biological aging of mammary epithelia may underpin breast cancer susceptibility ...

Discover how explainable AI enhances Parkinson’s disease prediction with improved accuracy and clinical interpretability.

For centuries, humans looked to seers and astrologers to determine fate. Today, we look to algorithms, and the loss of agency ...

Researchers conducted a systematic review to assess the risk of bias and applicability of prediction models for fear of recurrence in patients with cancer.

A biology-guided artificial intelligence model applied to routine pathology slides accurately predicted outcomes and response to immunotherapy in patients with metastatic non-small cell lung ...

Oregon Health & Science University researchers have developed a first-of-its-kind method to predict cancer patient survival ...

A biology-guided artificial intelligence model applied to routine pathology slides accurately predicted outcomes and response to ...

Glioblastoma, the most aggressive malignant brain tumor in adults, is not an isolated lesion, but a disease that destabilizes ...

This review examines how high-throughput proteomics is expanding precision medicine by improving biomarker discovery, disease ...