AIMC Topic: Cross-Sectional Studies

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Readiness towards artificial intelligence among medical and dental undergraduate students in Peshawar, Pakistan: a cross-sectional survey.

BMC medical education
INTRODUCTION: Artificial intelligence is a transformative tool for improving healthcare delivery and diagnostic accuracy in the medical and dental fields. This study aims to assess the readiness of future healthcare workers for artificial intelligenc...

Integrating prior knowledge with deep learning for optimized quality control in corneal images: A multicenter study.

Computer methods and programs in biomedicine
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...

Using machine learning approach to predict suicide ideation and suicide attempts among Chinese adolescents: A cross-sectional study.

Journal of affective disorders
BACKGROUND: Screening for suicide ideation and suicide attempts is crucial for adolescents, yet accurately predicting these outcomes remains a significant challenge. The relationship between non-suicidal self-injury and suicide ideation and attempts ...

A cross-sectional study on ChatGPT's alignment with clinical practice guidelines in musculoskeletal rehabilitation.

BMC musculoskeletal disorders
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
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 ...

Validating Emotion Analysis on Social Media Text for Detecting Psychological Distress: A Cross-Sectional Survey.

Issues in mental health nursing
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
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
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.