AIMC Topic: Cross-Sectional Studies
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Classifying Patient Complaints Using Artificial Intelligence-Powered Large Language Models: Cross-Sectional Study.
Journal of medical Internet research
Aug 6, 2025
BACKGROUND: Patient complaints provide valuable insights into the performance of health care systems, highlighting potential risks not apparent to staff. Patient complaints can drive systemic changes that enhance patient safety. However, manual categ...
Attitudes and readiness to adopt artificial intelligence among healthcare practitioners in Pakistan's resource-limited settings.
BMC health services research
Aug 6, 2025
BACKGROUND: Artificial Intelligence (AI) can empower clinicians to make data-driven decisions, treatments and streamline administrative tasks. However, it is vital to understand their perception towards AI for seamless implementation in practice. The...
Automated classification of skeletal malocclusion in German orthodontic patients.
Clinical oral investigations
Aug 5, 2025
OBJECTIVES: Precisely diagnosing skeletal class is mandatory for correct orthodontic treatment. Artificial intelligence (AI) could increase efficiency during diagnostics and contribute to automated workflows. So far, no AI-driven process can differen...
Prevalence, associated risk factors and satellite imagery analysis in predicting soil-transmitted helminth infection in Nakhon Si Thammarat Province, Thailand.
Scientific reports
Aug 4, 2025
Soil-transmitted helminth (STH) infections remain a significant public health concern in rural areas, often leading to nutritional and physical impairment, particularly in children. This study aimed to assess the prevalence and associated factors of ...
Markers of body fat, the mediating role of alanine aminotransferase, and their association with the risk of metabolic dysfunction-associated steatotic liver disease.
European journal of pediatrics
Aug 2, 2025
Metabolic dysfunction-associated steatotic liver disease (MASLD) in children with obesity correlates with metabolic dysfunction, yet interactions between anthropometrics, liver enzymes, and risk of MASLD remain unclear. This study included 219 childr...
METS-VF as a novel predictor of gallstones in U.S. adults: a cross-sectional analysis (NHANES 2017-2020).
BMC gastroenterology
Jul 31, 2025
BACKGROUND AND AIMS: Obesity is a well-established risk factor for gallstone formation, but traditional anthropometric measures (e.g., BMI, waist circumference) inadequately assess metabolically active visceral adiposity. The novel Metabolic Score fo...
Evaluating the Performance of State-of-the-Art Artificial Intelligence Chatbots Based on the WHO Global Guidelines for the Prevention of Surgical Site Infection: Cross-Sectional Study.
Journal of medical Internet research
Jul 31, 2025
BACKGROUND: Surgical site infection (SSI) is the most prevalent type of health care-associated infection that leads to increased morbidity and mortality and a significant economic burden. Effective prevention of SSI relies on surgeons strictly follow...
Association between atherogenic index of plasma and hypertension combined with diabetes mellitus in United States adults: an analysis of the NHANES surveys from 2011 to 2016.
Journal of health, population, and nutrition
Jul 30, 2025
INTRODUCTION: Observational studies have indicated that individuals with hypertension (HTN) and diabetes mellitus (DM) tend to exhibit elevated plasma atherogenic index of plasma (AIP), defined as log (triglyceride [TG]/high-density lipoprotein chole...
Predicting Engagement With Conversational Agents in Mental Health Therapy by Examining the Role of Epistemic Trust, Personality, and Fear of Intimacy: Cross-Sectional Web-Based Survey Study.
JMIR human factors
Jul 30, 2025
BACKGROUND: The use of conversational agents (CAs) in mental health therapy is gaining traction due to their accessibility, anonymity, and nonjudgmental nature. However, understanding the psychological factors driving preferences for CA-based therapy...
Readiness and Acceptance of Nursing Students Regarding AI-Based Health Care Technology on the Training of Nursing Skills in Saudi Arabia: Cross-Sectional Study.
JMIR nursing
Jul 30, 2025
BACKGROUND: The rapid advancements in artificial intelligence (AI) technologies across various sectors, including health care, necessitate the need for a comprehensive understanding of their applications. Specifically, the acceptance and readiness of...
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