Latest AI and machine learning research in health policy for healthcare professionals.
Telehealth has become a cornerstone of modern pediatric care, offering continuity, access and efficiency across a wide range of clinical settings. Initially a supplementary model, its rapid expansion during the COVID-19 pandemic accelerated innovation in virtual care delivery. Post-pandemic, pediatric telehealth remains a vital tool for improving access to behavioral health, chronic disease manage...
PURPOSE: In recent years, artificial intelligence-based language models have emerged as a means of rapid access to health-related information. This study aimed to evaluate the quality, reliability, understandability, and readability of ChatGPT's responses to frequently asked questions by families of children with cerebral palsy (CP). METHODS: Responses generated by the free version of ChatGPT to t...
BACKGROUND: Machine learning (ML) has been demonstrated to enhance health care cost prediction by handling high-dimensional data and identifying compl...
Foundation models are widely used for compressing complex data into vector embeddings (vembs), offering reduced storage and computational efficiency, ...
BACKGROUND: Artificial intelligence (AI) has the potential to improve cancer care. Its implementation must align with patients' needs, values, and liv...
Advances in digital pathology, image analysis, and artificial intelligence (AI) are rapidly transforming how pathologists and researchers interact wit...
BACKGROUND: Large language model (LLM)-based AI teaching agents are increasingly used in medical education, yet their pedagogical quality is typically...
BACKGROUND: Screening is important for early detection of cervical cancer in low- and middle-income countries. Visual inspection with acetic acid (VIA...
PURPOSE: Precision medicine, also known as personalized medicine, enables the provision of tailored health services to patients. In the prevention, ea...
This study integrates deep reinforcement learning (DRL) with lean management for renewable energy project scheduling. The problem is formulated as a c...
Essential services are necessary for individuals to recover from and adapt to disruptive events, yet the relationship between access to such services ...
The use of Patient-Reported Outcome Measures (PROMs) and Patient-Reported Experience Measures (PREMs) in cardiovascular disease (CVD) healthcare is an...
Rapid advances in artificial intelligence, sensor technologies, and image recognition have accelerated the transition toward digital and intelligent s...
BACKGROUND: Health economic modeling is conceptually sophisticated but operationally repetitive and resource intensive. Recent advances in large langu...
Artificial intelligence (AI) is rapidly compressing the timeline from molecular discovery to regulatory submission, meaning pipeline therapies will re...
BACKGROUND: Artificial intelligence (AI) methods are increasingly used to strengthen policy evaluation in managed care pharmacy. Among Medicare benefi...
BACKGROUND: Prior authorization (PA) is intended to support appropriate use and spending of services and medications, yet 1 in 6 insured adults report...
AIM: To compare the multidimensional performance of discharge instructions generated by generative AI (GPT-4) versus those created by clinical registe...
Uniportal full-endoscopic spine surgery (FESS) has expanded over three decades from percutaneous discectomy to include multilevel decompression, endos...
Smartphone-based fundus imaging (SBFI) is an emerging approach with potential relevance for global ophthalmic care, including in low- and middle-incom...