JAMA Network Open

Cost-effectiveness of Artificial Intelligence as a Decision-Support System Applied to the Detection and Grading of Melanoma, Dental Caries, and Diabetic Retinopathy

Objective  To assess the cost-effectiveness of artificial intelligence (AI) for supporting clinicians in detecting and grading diseases in dermatology, dentistry, and ophthalmology. Importance  AI has been referred to as a facilitator for more precise, personalized, and safer health care, and AI algorithms…

Diabetic Retinopathy Screening Among Federally Qualified Health Center Patients Using Point-of-Care AI – DRES-POCAI: A Trial Protocol

Importance  Diabetic retinopathy screening (DRS) rates have historically been low among underserved populations due to barriers in accessing traditional eye care. Although artificial intelligence (AI)–powered DRS provides a potential strategy to improve screening rates, its optimal integration into primary care workflows…

Adherence to the Planetary Health Diet Index and Fetal Body Composition

Importance  The Planetary Health Diet (PHD), introduced by the EAT-Lancet Commission in 2019, emphasizes a plant-based diet. Several cohorts have assessed adherence using the PHD Index (PHDI), but evidence is limited on whether maternal periconceptional and early pregnancy adherence is associated with…

Vulnerability of Large Language Models to Prompt Injection When Providing Medical Advice

Importance  Large language models (LLMs) are increasingly integrated into health care applications; however, their vulnerability to prompt-injection attacks (ie, maliciously crafted inputs that manipulate an LLM’s behavior) capable of altering medical recommendations has not been systematically evaluated. Objective  To evaluate the susceptibility…