AIMC Topic: Reproducibility of Results
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A Quantitative Study of Factors Influencing Myasthenia Gravis Telehealth Examination Score.
Muscle & nerve
Apr 2, 2025
INTRODUCTION/AIMS: The adoption of telemedicine is generally considered as advantageous for patients and physicians, but there is limited rigorous assessment of examination strengths and limitations. We set out to perform a quantitative assessment of...
A validity and reliability study of the artificial intelligence attitude scale (AIAS-4) and its relationship with social media addiction and eating behaviors in Turkish adults.
BMC public health
Apr 2, 2025
BACKGROUND: In recent years, there has been a rapid increase in the use of the internet and social media. Billions of people worldwide use social media and spend an average of 2.2 h a day on these platforms. At the same time, artificial intelligence ...
Machine learning in point-of-care testing: innovations, challenges, and opportunities.
Nature communications
Apr 2, 2025
The landscape of diagnostic testing is undergoing a significant transformation, driven by the integration of artificial intelligence (AI) and machine learning (ML) into decentralized, rapid, and accessible sensor platforms for point-of-care testing (...
Development and Validation of a Machine Learning Model for Early Prediction of Delirium in Intensive Care Units Using Continuous Physiological Data: Retrospective Study.
Journal of medical Internet research
Apr 2, 2025
BACKGROUND: Delirium in intensive care unit (ICU) patients poses a significant challenge, affecting patient outcomes and health care efficiency. Developing an accurate, real-time prediction model for delirium represents an advancement in critical car...
Advanced imaging techniques and artificial intelligence in pleural diseases: a narrative review.
European respiratory review : an official journal of the European Respiratory Society
Apr 2, 2025
BACKGROUND: Pleural diseases represent a significant healthcare burden, affecting over 350 000 patients annually in the US alone and requiring accurate diagnostic approaches for optimal management. Traditional imaging techniques have limitations in d...
Application of type-2 heptagonal fuzzy sets with multiple operators in multi-criteria decision-making for identifying risk factors of Zika virus.
BMC infectious diseases
Apr 1, 2025
PURPOSE: This study aims to identify and rank the key risk factors associated with the Zika virus by leveraging a novel multi-criteria decision-making (MCDM) framework based on type-2 heptagonal fuzzy sets. By integrating advanced aggregation operato...
Semi-supervised spatial-frequency transformer for metal artifact reduction in maxillofacial CT and evaluation with intraoral scan.
European journal of radiology
Mar 31, 2025
PURPOSE: To develop a semi-supervised domain adaptation technique for metal artifact reduction with a spatial-frequency transformer (SFTrans) model (Semi-SFTrans), and to quantitatively compare its performance with supervised models (Sup-SFTrans and ...
Automated generation of echocardiography reports using artificial intelligence: a novel approach to streamlining cardiovascular diagnostics.
The international journal of cardiovascular imaging
Mar 31, 2025
Accurate interpretation of echocardiography measurements is essential for diagnosing cardiovascular diseases and guiding clinical management. The emergence of large language models (LLMs) like ChatGPT presents a novel opportunity to automate the gene...
The reality of modeling irritable bowel syndrome: progress and challenges.
Expert opinion on drug discovery
Mar 31, 2025
INTRODUCTION: Irritable bowel syndrome (IBS) is a common gastrointestinal disorder that is often therapeutically challenging. While research has advanced our understanding of IBS pathophysiology, developing precise models to predict drug response and...
Integrating deep learning with ECG, heart rate variability and demographic data for improved detection of atrial fibrillation.
Open heart
Mar 31, 2025
BACKGROUND: Atrial fibrillation (AF) is a common but often undiagnosed condition, increasing the risk of stroke and heart failure. Early detection is crucial, yet traditional methods struggle with AF's transient nature. This study investigates how au...
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