Latest AI and machine learning research in health policy for healthcare professionals.
Older adults represent most patients with cancer worldwide, yet they remain substantially underrepresented in randomized clinical trials (RCTs), limiting the evidence available to guide treatment decisions in this growing population. Real-world data (RWD), defined as data routinely collected from clinical practice such as electronic health records, administrative claims, clinical registries, weara...
Regulatory agencies require comprehensive genotoxicity assessments for novel small-molecule therapeutics prior to human trials. Developers often delay these studies until a candidate is nearing regulatory submission because they are expensive and secondary to bioactivity. This timing creates a bottleneck where late-stage failures can jeopardize >$10 million in capital and multiple years of develop...
In the era of digital transformation characterized by the deep integration of artificial intelligence and the Internet of Things, human-machine intera...
OBJECTIVES: To evaluate the quality, patient-centeredness, clinician endorsement, and readability of generative artificial intelligence (AI) responses...
The international human right to health states that people have claims to access goods, services, and infrastructure that protects an adequate standar...
BACKGROUND: Feedback is fundamental to health professions education and essential for workplace-based assessment. Unfortunately, most educators lack f...
BACKGROUND: Palliative care improves the quality of life of people living with life-limiting conditions and their families; however, global access rem...
This cross-sectional study aimed to investigate the combined effects of chronotype, Mediterranean diet adherence, and sleep quality on mental distress...
PURPOSE: Percutaneous nephrolithotomy (PCNL) is the gold standard for treating large and complex renal calculi, but puncture path selection (papillary...
PURPOSE: To evaluate the diagnostic performance of a general-purpose vision-language model (GPT-4o) in interpreting gonioscopic images of the anterior...
OBJECTIVES: To propose an equity-by-design agenda for socially assistive robots (SARs) as embodied digital health informatics interventions. MATERIALS...
Artificial intelligence (AI) is transforming drug discovery and development, fields historically constrained by long timelines, high costs, and substa...
BACKGROUND: The implementation of digital technologies within health services promises increased performance, quality, and efficiency. However, eviden...
BACKGROUND: Healthcare professionals other than dietitians are widely perceived as credible sources of nutrition information by patients, despite many...
BACKGROUND: Effective health care communication is crucial in the medical field. However, effective communication in clinical practice still faces num...
Amid the progression of an aging society, it is essential to develop a long-term predictive model capable of distinguishing between older adults with ...
BACKGROUND: The use of artificial intelligence and machine learning (ML) tools is now common in the advancement of health care services and clinical r...
BACKGROUND: Effective communication about breast and cervical cancers remains a public health challenge, with widespread misinformation and barriers t...
BACKGROUND: Most US health systems operate on a local or regional scale and face substantial financial and staffing pressures, which are intensified b...
Artificial intelligence (AI) tools in diabetic retinal screening (DRS) are currently in use overseas within public health systems, with growing eviden...