Articles related to ARTIFICIAL INTELLIGENCE (AI)

Personalized models using wearable data forecast sedentary bouts in women with chronic pelvic pain, primarily endometriosis. Simpler models performed comparably to deep learning, but benefits from prediction-guided movement prompts remain untested.

Healthcare leaders speaking at AXS26 argued that artificial intelligence tools affecting patient care require stronger oversight, including independent validation, bias monitoring, and human review. The discussion highlighted both operational opportunities and safety concerns surrounding healthcare AI adoption.

Artificial intelligence tools are increasingly being integrated into prostate cancer imaging, pathology, prognostication, and treatment planning. Although several platforms have demonstrated promising accuracy and workflow benefits, broad clinical adoption will require prospective validation, regulatory oversight, and careful implementation.

As generative artificial intelligence enters neurology practice, professional organizations and emerging evidence emphasize physician oversight, documentation, privacy compliance, and independent clinical judgment amid ongoing concerns about hallucinations, liability, and patient safety.

An AI-enabled fetal monitoring alert system alone did not improve management of uterine tachysystole, but pairing the system with nurse education was associated with more timely evidence-based interventions. Improvements in tachysystole incidence were not observed.

A nursing educator argues that workforce demands, competency-based education, and generative AI are exposing long-standing tensions in nursing education. The commentary questions whether current models adequately prepare graduates for modern practice realities.