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Gender Differences in Predicting Metabolic Syndrome Among Hospital Employees Using Machine Learning Models: A Population-Based Study.
The journal of nursing research : JNR
Apr 1, 2025
BACKGROUND: Metabolic syndrome (MetS) is a complex condition that captures several markers of dysregulation, including obesity, elevated blood glucose levels, dyslipidemia and hypertension. Using an approach to early prediction of MetS risk in hospit...
Artificial Intelligence-Enhanced Perfusion Scoring Improves the Diagnostic Accuracy of Myocardial Perfusion Imaging.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Apr 1, 2025
We previously demonstrated that a deep learning (DL) model of myocardial perfusion SPECT imaging improved accuracy for detection of obstructive coronary artery disease (CAD). We aimed to improve the clinical translatability of this artificial intelli...
Development, validation, and clinical evaluation of a machine-learning based model for diagnosing early infection after cardiovascular surgery (DEICS): a multi-center cohort study.
International journal of surgery (London, England)
Apr 1, 2025
BACKGROUND: This study addresses the critical need for timely and accurate diagnosis of early postoperative infection (EPI) following cardiac surgery. EPI significantly impacts patient outcomes and healthcare costs, making its early detection vital.
Multiparametric MRI and transfer learning for predicting positive margins in breast-conserving surgery: a multi-center study.
International journal of surgery (London, England)
Apr 1, 2025
This study aimed to predict positive surgical margins in breast-conserving surgery (BCS) using multiparametric MRI (mpMRI) and radiomics. A retrospective analysis was conducted on data from 444 BCS patients from three Chinese hospitals between 2019 a...
Construction of an artificially intelligent model for accurate detection of HCC by integrating clinical, radiological, and peripheral immunological features.
International journal of surgery (London, England)
Apr 1, 2025
BACKGROUND: Integrating comprehensive information on hepatocellular carcinoma (HCC) is essential to improve its early detection. We aimed to develop a model with multimodal features (MMF) using artificial intelligence (AI) approaches to enhance the p...
Machine Learning-Guided Fluid Resuscitation for Acute Pancreatitis Improves Outcomes.
Clinical and translational gastroenterology
Apr 1, 2025
INTRODUCTION: Ariel Dynamic Acute Pancreatitis Tracker (ADAPT) is an artificial intelligence tool using mathematical algorithms to predict severity and manage fluid resuscitation needs based on the physiologic parameters of individual patients. Our a...
Cardiometabolic index predicts cardiovascular events in aging population: a machine learning-based risk prediction framework from a large-scale longitudinal study.
Frontiers in endocrinology
Apr 1, 2025
BACKGROUND: While the Cardiometabolic Index (CMI) serves as a novel marker for assessing adipose tissue distribution and metabolic function, its prognostic utility for cardiovascular disease (CVD) events remains incompletely understood. This investig...
Barriers and enablers for the deployment of large language model-based conversational robots for older adults: A protocol for a systematic review of qualitative studies.
PloS one
Apr 1, 2025
BACKGROUND: Artificial intelligence-powered conversational agents have immense potential to provide social companionship and support for older adults. However, the deployment of large language model (LLM)-based conversational robots for seniors faces...
Predicting a failure of postoperative thromboprophylaxis in non-small cell lung cancer: A stacking machine learning approach.
PloS one
Apr 1, 2025
BACKGROUND: Non-small-cell lung cancer (NSCLC) and its surgery significantly increase the venous thromboembolism (VTE) risk. This study explored the VTE risk factors and established a machine-learning model to predict a failure of postoperative throm...
Comprehensive Analysis of Heart Failure Subtypes Presenting at Emergency Department for Acute Heart Failure Management.
Journal of emergency nursing
Mar 31, 2025
INTRODUCTION: Despite advances in echocardiography and biomarkers, the pathophysiological complexities among heart failure categories remain incompletely understood. This study analyzed patients' characteristics across heart failure with reduced ejec...
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