Using routine clinical data, the model gauges liver cancer risk better than existing tools, offering a potential way to identify high-risk patients missed by current screening criteria.

For its 2nd anniversary, Callisto DataHub offers free annotated datasets of 50 suspected lung cancer X-rays and 50 ...

Artificial intelligence (AI) could help physicians determine if survivors of childhood cancer need extra support - and the more information included in AI prompting, the better its performance. This ...

A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), the most common ...

Drug resistance remains a central barrier to durable responses across cancer therapies, spanning targeted agents, cytotoxic chemotherapy, endocrine ...

Researchers assessed the feasibility of using large language models to match cancer patients with certain genetic mutations to appropriate clinical trials.

Skolnick has developed AI-based approaches to predict protein structure and function that may help with drug discovery and ...

The integration of bioinformatics and medical imaging, often referred to as radiogenomics, has emerged as a powerful and transformative approach in cancer ...