AIMC Topic: Aged
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Deep learning radiomics for the prediction of epidermal growth factor receptor mutation status based on MRI in brain metastasis from lung adenocarcinoma patients.
BMC cancer
Mar 12, 2025
BACKGROUND: Early and accurate identification of epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC) patients with brain metastases is critical for guiding targeted therapy. This study aimed to develop a deep...
Development and validation of machine learning models for predicting extubation failure in patients undergoing cardiac surgery: a retrospective study.
Scientific reports
Mar 12, 2025
Patients with multiple comorbidities and those undergoing complex cardiac surgery may experience extubation failure and reintubation. The aim of this study was to establish an extubation prediction model using explainable machine learning and identif...
Machine learning analysis of integrated ABP and PPG signals towards early detection of coronary artery disease.
Scientific reports
Mar 12, 2025
Every year, Coronary Artery Disease (CAD) claims lives of over a million people. CAD occurs when the coronary arteries, responsible for supplying oxygenated blood to the heart, get occluded due to plaque deposits on their inner walls. The most critic...
Assessing Total Hip Arthroplasty Outcomes and Generating an Orthopedic Research Outcome Database via a Natural Language Processing Pipeline: Development and Validation Study.
JMIR medical informatics
Mar 12, 2025
BACKGROUND: Processing data from electronic health records (EHRs) to build research-grade databases is a lengthy and expensive process. Modern arthroplasty practice commonly uses multiple sites of care, including clinics and ambulatory care centers. ...
Patient Perspectives on Conversational Artificial Intelligence for Atrial Fibrillation Self-Management: Qualitative Analysis.
Journal of medical Internet research
Mar 12, 2025
BACKGROUND: Conversational artificial intelligence (AI) allows for engaging interactions, however, its acceptability, barriers, and enablers to support patients with atrial fibrillation (AF) are unknown.
Neuropsychological tests and machine learning: identifying predictors of MCI and dementia progression.
Aging clinical and experimental research
Mar 12, 2025
BACKGROUND: Early prediction of progression in dementia is of major importance for providing patients with adequate clinical care, with considerable impact on the organization of the whole healthcare system.
Querying the capability of the post-HoLEP endoscopic aspect of the membranous urethral mucosa in predicting urinary incontinence: a prospective AI-based analysis.
World journal of urology
Mar 12, 2025
INTRODUCTION: Transient stress urinary incontinence (SUI) after holmium laser enucleation of prostate (HoLEP) is commonly linked to intraoperative injury of the external urethral sphincter (EUS). We assessed the reliability of the post-HoLEP endoscop...
Development of a machine learning-based predictive model for maxillary sinus cysts and exploration of clustering patterns.
Head & face medicine
Mar 12, 2025
BACKGROUND AND OBJECTIVE: There are still many controversies about the factors influencing maxillary sinus cysts and their clinical management. This study aims to construct a prediction model of maxillary sinus cyst and explore its clustering pattern...
Deep learning based automatic quantification of aortic valve calcification on contrast enhanced coronary CT angiography.
Scientific reports
Mar 12, 2025
Quantifying aortic valve calcification is critical for assessing the severity of aortic stenosis, predicting cardiovascular risk, and guiding treatment decisions. This study evaluated the feasibility of a deep learning-based automatic quantification ...
Development of a visualized risk prediction system for sarcopenia in older adults using machine learning: a cohort study based on CHARLS.
Frontiers in public health
Mar 12, 2025
INTRODUCTION: The older adult are at high risk of sarcopenia, making early identification and scientific intervention crucial for healthy aging.
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