AIMC Topic: Adult

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Clinical Performance and Communication Skills of ChatGPT Versus Physicians in Emergency Medicine: Simulated Patient Study.

JMIR medical informatics
BACKGROUND: Emergency medicine can benefit from artificial intelligence (AI) due to its unique challenges, such as high patient volume and the need for urgent interventions. However, it remains difficult to assess the applicability of AI systems to r...

Deep Learning-Based Precision Cropping of Eye Regions in Strabismus Photographs: Algorithm Development and Validation Study for Workflow Optimization.

Journal of medical Internet research
BACKGROUND: Traditional ocular gaze photograph preprocessing, relying on manual cropping and head tilt correction, is time-consuming and inconsistent, limiting artificial intelligence (AI) model development and clinical application.

Self-Disclosure and Social Support in a Web-Based Opioid Recovery Community: Machine Learning Analysis.

JMIR formative research
BACKGROUND: The opioid crisis remains a critical public health challenge, with opioid use disorder (OUD) imposing significant societal and health care burdens. Web-based communities, such as the Reddit community r/OpiatesRecovery, provide an anonymou...

Embracing AI in academia: A mixed methods study of nursing students' and educators' perspectives on using ChatGPT.

PloS one
BACKGROUND: The integration of artificial intelligence (AI) tools such as ChatGPT is reshaping academic practice, particularly in nursing education. Understanding how nursing students and educators perceive and interact with ChatGPT is essential for ...

Deep learning-based detection of depression by fusing auditory, visual and textual clues.

Journal of affective disorders
BACKGROUND: Early detection of depression is crucial for implementing interventions. Deep learning-based computer vision (CV), semantic, and acoustic analysis have enabled the automated analysis of visual and auditory signals.

Predicting treatment-seeking status for alcohol use disorder using polygenic scores and machine learning in a deeply-phenotyped sample.

Drug and alcohol dependence
BACKGROUND: Few individuals with alcohol use disorder (AUD) receive treatment. Previous studies have shown drinking behavior, psychological problems, and substance dependence to predict treatment seeking. However, to date, no studies have incorporate...

Which explanations do clinicians prefer? A comparative evaluation of XAI understandability and actionability in predicting the need for hospitalization.

BMC medical informatics and decision making
BACKGROUND: This study aims to address the gap in understanding clinicians' attitudes toward explainable AI (XAI) methods applied to machine learning models using tabular data, commonly found in clinical settings. It specifically explores clinicians'...

Knowledge and perception of artificial lntelligence education among undergraduate healthcare students.

BMC medical education
BACKGROUND: Artificial intelligence (AI) is gaining recognition for its ability to enhance patient outcomes in healthcare. Therefore, integrating AI into the undergraduate curriculum is essential to equip students with foundational knowledge before g...

Comparative study of 2D vs. 3D AI-enhanced ultrasound for fetal crown-rump length evaluation in the first trimester.

BMC pregnancy and childbirth
BACKGROUND: Accurate fetal growth evaluation is crucial for monitoring fetal health, with crown-rump length (CRL) being the gold standard for estimating gestational age and assessing growth during the first trimester. To enhance CRL evaluation accura...

An end-to-end interpretable machine-learning-based framework for early-stage diagnosis of gallbladder cancer using multi-modality medical data.

BMC cancer
BACKGROUND: The accurate early-stage diagnosis of gallbladder cancer (GBC) is regarded as one of the major challenges in the field of oncology. However, few studies have focused on the comprehensive classification of GBC based on multiple modalities....