Latest AI and machine learning research in surveys for healthcare professionals.
TOPIC: Artificial intelligence (AI) is increasingly applied to support decision-making in ophthalmology. This review evaluates the ability of AI to predict postoperative outcomes after anterior segment and ocular adnexal procedures. CLINICAL RELEVANCE: The prognostic application of AI algorithms, capable of handling multimodal, complex data, and modeling nonlinear relationships, may enhance periop...
Artificial intelligence (AI) is increasingly implemented in medical education, adding new opportunities to improve learning in complex subjects like anatomy. This study assessed the perceived effectiveness of AI-powered tools in undergraduate anatomy education by evaluating the content validity of AI-generated materials, the student-perceived quality of generated questions, and students' perceptio...
OBJECTIVE: Large language models (LLMs) have been explored for clinical applications, yet their reliability in pediatric electrocardiogram (ECG) inter...
Accurate prediction of non-Newtonian nanofluid flow and heat transfer under melting heat conditions is essential for applications in advanced thermal ...
BACKGROUND: Chatbots have recently emerged as an alternative approach for delivering cancer risk assessment and genetic counseling. Understanding the ...
Background and Purpose: The rapid expansion of artificial intelligence in health care is reshaping clinical workflows and decision-making, making it i...
Oropharyngeal dysphagia (OD) is highly prevalent (35.6%-47.4%) in hospitalized older patients but clinical screening is slow and labor-intensive, lead...
BACKGROUND: Digital technologies - including computer-aided design and manufacturing systems, three-dimensional printing, digital radiography, intraor...
BACKGROUND: Artificial intelligence (AI) is rapidly transforming healthcare. Current and future healthcare workforce, including nursing students, requ...
BACKGROUND: The potential influence of the initial child-dentist interaction on dental anxiety (DA) in preschool children remains insufficiently under...
The diagnostic image quality of positron emission tomography (PET) acquisitions strongly depends on the administered radiotracer activity and acquisit...
BACKGROUND: As artificial intelligence (AI) chatbots become an increasingly common source of quick medical guidance, it is important to understand whe...
BACKGROUND: Alcohol use remains a major public health concern, and although preventive alcohol self-help interventions aim to support individuals in n...
OBJECTIVES: Systematic literature reviews (SLRs) underpin life sciences research but are resource intensive. Generative artificial intelligence, parti...
OBJECTIVES: Electronic health record (EHR) data discontinuity, defined as receiving care outside of a particular EHR system, may cause misclassificati...
BACKGROUND: Accurate assessment of caries depth on intraoral radiographs is crucial for determining the extent of the lesion and planning appropriate ...
RATIONALE: After inadequate response to first-line biologic or targeted synthetic (b/ts) disease-modifying antirheumatic drug (DMARD) therapy in adult...
Machine learning models built from national health surveys enable population-scale risk stratification, yet the GDPR's "right to be forgotten" mandate...
BACKGROUND: Lyme disease (LD) is the most common vector-borne disease in the United States. It is difficult to diagnose because it can mimic numerous ...
BACKGROUND: With the growing integration of generative Artificial Intelligence (AI) into healthcare, the DeepSeek large language model has emerged as ...