Category: ARTIFICIAL INTELLIGENCE

AI tool debuts with better genomic predictions and explanations

February 19, 2026

Artificial intelligence has taken the world by storm. In biology, AI tools called deep neural networks (DNNs) have proven invaluable for predicting the results of genomic experiments. Their usefulness has these tools poised to set the stage for efficient, AI-guided research and potentially lifesaving discoveries—if scientists can work out the kinks. The findings are published in the journal npj Artificial Intelligence.

Machine-learned biomarker identifies those at high risk for liver cancer

February 18, 2026

Researchers led by Xian-Yang Qin at the RIKEN Center for Integrative Medical Sciences (IMS) in Japan have developed a score that predicts the risk of liver cancer. Published in the journal Proceedings of the National Academy of Sciences, the study establishes that the protein MYCN drives liver tumorigenesis, specifically of the type of tumors found in the deadliest subtype of liver cancer.

AI-powered liquid biopsy can classify pediatric brain tumors with 92% accuracy

February 17, 2026

St. Jude Children’s Research Hospital scientists, in collaboration with scientists at the Hopp Children’s Cancer Center Heidelberg (KiTZ), German Cancer Research Center (DKFZ) and other international centers, created Methylation-based Predictive Algorithm for CNS Tumors (M-PACT). M-PACT uses AI to sift through ctDNA in cerebrospinal fluid and molecularly classify tumors based on their DNA methylation pattern.

AI model flags insulin resistance as a risk factor for 12 cancers

February 16, 2026

For the first time, researchers, including those from the University of Tokyo, applied a machine learning-based prediction model of insulin resistance to half a million participants from the UK Biobank and demonstrated that insulin resistance is a risk factor for 12 types of cancer.

AI model may predict when MND patients need feeding tubes within months

February 12, 2026

A new AI tool that accurately predicts the need for a feeding tube could transform patient care and improve quality of life for people living with Motor Neuron Disease (MND).

AI-built maps reveal causal gene regulation across Alzheimer’s brain cell types

February 12, 2026

Researchers led by Min Zhang and Dabao Zhang of the University of California, Irvine’s Joe C. Wen School of Population & Public Health have created the most detailed maps to date showing how genes causally regulate one another across different types of brain cells affected by Alzheimer’s disease.