AIMC Topic: Cross-Sectional Studies
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Integrating prior knowledge with deep learning for optimized quality control in corneal images: A multicenter study.
Computer methods and programs in biomedicine
Apr 28, 2025
OBJECTIVE: Artificial intelligence (AI) models are effective for analyzing high-quality slit-lamp images but often face challenges in real-world clinical settings due to image variability. This study aims to develop and evaluate a hybrid AI-based ima...
A cross-sectional study on ChatGPT's alignment with clinical practice guidelines in musculoskeletal rehabilitation.
BMC musculoskeletal disorders
Apr 24, 2025
BACKGROUND: AI models like ChatGPT have the potential to support musculoskeletal rehabilitation by providing clinical insights. However, their alignment with evidence-based guidelines needs evaluation before integration into physiotherapy practice.
Decoding vital variables in predicting different phases of suicide among young adults with childhood sexual abuse: a machine learning approach.
Translational psychiatry
Apr 24, 2025
Young adults with childhood sexual abuse (CSA) are an especially vulnerable group to suicide. Suicide encompasses different phases, but for CSA survivors the salient factors precipitating suicide are rarely studied. In this study, from a progressive ...
Identification of Risk Group for Root Caries and Analysis of Associated Factors in Older Adults Using Unsupervised Machine Learning Clustering.
Clinical interventions in aging
Apr 24, 2025
PURPOSE: This study aimed to identify the high-risk group for root caries using unsupervised machine learning and to explore the associated factors.
Validating Emotion Analysis on Social Media Text for Detecting Psychological Distress: A Cross-Sectional Survey.
Issues in mental health nursing
Apr 23, 2025
This study investigates the relationship between self-reported psychological distress and emotions in social media posts, using a deep learning-based emotion analysis model. A cross-sectional design was used, collecting data from Instagram and Thread...
Deep learning approach in undergraduate nursing students and their relationship with learning outcomes: A latent profile analysis.
Nurse education in practice
Apr 23, 2025
BACKGROUND: Deep learning approach plays a pivotal role in nursing education, equipping students with the critical thinking skills and knowledge necessary to address complex clinical challenges. However, nursing students exhibit diverse approaches to...
Integrating AI in medical education: a comprehensive study of medical students' attitudes, concerns, and behavioral intentions.
BMC medical education
Apr 23, 2025
BACKGROUND: To analyze medical students' perceptions, trust, and attitudes toward artificial intelligence (AI) in medical education, and explore their willingness to integrate AI in learning and teaching practices.
Expectations of Intensive Care Physicians Regarding an AI-Based Decision Support System for Weaning From Continuous Renal Replacement Therapy: Predevelopment Survey Study.
JMIR medical informatics
Apr 23, 2025
BACKGROUND: Critically ill patients in intensive care units (ICUs) require continuous monitoring, generating vast amounts of data. Clinical decision support systems (CDSS) leveraging artificial intelligence (AI) technologies have shown promise in imp...
The inconsistent pathogenesis of endometriosis and adenomyosis: insights from endometrial metabolome and microbiome.
mSystems
Apr 22, 2025
UNLABELLED: Endometriosis (EM) and adenomyosis (AM) are interrelated gynecological disorders characterized by the aberrant presence of endometrial tissue and are frequently linked with chronic pelvic pain and infertility, yet their pathogenetic mecha...
Artificial intelligence based assessment of clinical reasoning documentation: an observational study of the impact of the clinical learning environment on resident documentation quality.
BMC medical education
Apr 22, 2025
BACKGROUND: Objective measures and large datasets are needed to determine aspects of the Clinical Learning Environment (CLE) impacting the essential skill of clinical reasoning documentation. Artificial Intelligence (AI) offers a solution. Here, the ...
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