In an era where technology continues to evolve at a staggering pace, the integration of algorithms into healthcare decisions holds both promise and peril. Over the last few decades, the role of ...

Health systems have a large amount of patient data through EHRs and other digital platforms managing administrative tasks and clinical care. The de-identified patient data is useful for creating large ...

California is taking aim at algorithms used by insurers to make prior authorization and other coverage decisions with a new law that will put limitations on how artificial intelligence (AI)–generated ...

A machine-learning algorithm can use demographic, symptomatic, and clinical data to accurately predict the health-related quality of life (QoL) of patients with kidney stones, new research shows.

Health care data exists in many forms, from medical records held in health care facilities to information captured through daily routines and lifestyle choices. This includes vital signs, medication ...

Categorizing patients with cancer by their disease stage can be an important tool when conducting administrative claims-based studies. As claims databases frequently do not capture this information, ...

The application of artificial intelligence (AI) for healthcare is transforming patient treatment, from advanced analytics to computerized automated diagnosis. However, with the increased application ...

A research team evaluated the reliability of human experts in comparison to an automated algorithm in assessing the quality of intracranial electroencephalography (iEEG) data. Published in the Journal ...