Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...

I have this idea of a communal brain.” David Baker, PhD, told me as I sat in his office at the University of Washington (UW) ...

Genomic surveillance—the process of monitoring and sequencing pathogens—is one of the most important tools for detecting ...

Cancer immunotherapy drugs known as immune checkpoint inhibitors (ICIs) can be miracle drugs for cancer patients, curing some and turning deadly disease into a manageable chronic condition in others.

Since 2017, Iason Gabriel has worked at the tech giant, trying to anticipate – and think through – the impact of AI. But as commercial and geopolitical pressures escalate, can ethicists make any ...

The class of drugs known as DNA Damage Response inhibitors, which work by blocking cancer cells’ ability to repair their own damaged DNA, is expanding rapidly beyond its original anchor, the PARP ...

Abstract: Predicting individual behavior from brain imaging data using machine learning is a rapidly growing field in neuroscience. Functional connectivity (FC), which captures interactions between ...

An efficient, ready‑to‑use workflow from whole‑slide image to biomarker prediction. STAMP is an end‑to‑end, weakly‑supervised deep‑learning pipeline that helps discover and evaluate candidate ...

A study explores how AI and ML can improve early detection of neurological diseases, including Parkinson’s disease, ...

Artificial intelligence (AI) is helping nurses better predict health problems before they become emergencies, according to a ...

The Martin-Hopkins equation to assess low-density lipoprotein (LDL) cholesterol levels in blood samples has been used by ...