AIMC Topic: Cross-Sectional Studies

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Evaluating community resilience through social media during China's first post-COVID-19 reopening: insights from machine learning.

Journal of global health
BACKGROUND: In the face of pandemics from infectious diseases, enhancing community resilience is increasingly important. It is, therefore, essential to evaluate community resilience and identify factors that can strengthen it. This study aimed to eva...

Data-driven cluster analysis identifies three clinical phenotypes in hemodialysis patients.

Renal failure
Clinical heterogeneity among hemodialysis patients necessitates precision medicine approaches transcending conventional single-parameter management. Through machine learning analysis of 1,207 maintenance hemodialysis patients, we developed a novel tw...

Leveraging Large Language Models to Identify Engagement-Driving Features in Vaping-Related TikTok Videos: Cross-Sectional Study.

Journal of medical Internet research
BACKGROUND: Electronic cigarette (e-cigarette) use is prevalent in youth and young adults in the United States. TikTok (ByteDance), a popular social media platform among youth and young adults, has become a key avenue for disseminating e-cigarette-re...

Teaching Clinical Reasoning in Health Care Professions Learners Using AI-Generated Script Concordance Tests: Mixed Methods Formative Evaluation.

JMIR formative research
BACKGROUND: The integration of artificial intelligence (AI) in medical education is evolving, offering new tools to enhance teaching and assessment. Among these, script concordance tests (SCTs) are well-suited to evaluate clinical reasoning in contex...

Biological Age Prediction of the Cerebellar Vermis in the Human Lifespan.

Cerebellum (London, England)
The cerebellar vermis undergoes diverse structural changes with aging, yet region-specific aging patterns remain underexplored. Using Brain Structure Age (BSA), a deep learning biomarker from structural magnetic resonance imaging (MRI), we aimed to: ...

Comparative performance of large language models in answering periodontology questions from the Turkish Dental Specialty Examination: a cross-sectional study on accuracy and coverage.

BMC oral health
BACKGROUND: In recent years, several studies have explored the use of large language models (LLMs) such as ChatGPT-4, Claude, Gemini Advanced, and DeepSeek-R1 in dental education. Nevertheless, no study has yet reported a comparative evaluation of mu...

Using Machine Learning Methods to Examine Turnover Rates in State Health Agencies.

Journal of public health management and practice : JPHMP
CONTEXT: High turnover rates in the public health workforce pose ongoing challenges to maintain essential services and institutional knowledge. Recent studies indicate that job dissatisfaction, burnout, and structural barriers have intensified follow...

Relationship between C-reactive protein triglyceride glucose index and cardiovascular disease risk: a cross-sectional analysis with machine learning.

BMC medical informatics and decision making
BACKGROUND: Cardiovascular disease (CVD) continues to be a leading cause of disease burden and mortality worldwide. Identifying reliable biomarkers for CVD risk assessment is essential. This study investigates the association between the C-reactive p...

Unveiling the burden of snakebite injuries: an EQ-5D-5 L-based evaluation of health-related quality of life.

BMC public health
BACKGROUND: Snakebite envenoming remains poorly understood in terms of long-term health-related quality of life (HRQoL), particularly in China where standardized assessments are lacking. This study is the first to comprehensively evaluate HRQoL impai...

Perceptions of portable dentistry in Asia using machine learning models.

Scientific reports
Access to healthcare is a significant challenge for individuals with limited mobility, particularly in developing countries and among vulnerable populations in Asia. Portable dentistry offers an innovative solution by delivering essential dental serv...