AIMC Topic: Aged
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Automated stenosis estimation of coronary angiographies using end-to-end learning.
The international journal of cardiovascular imaging
Jan 9, 2025
The initial evaluation of stenosis during coronary angiography is typically performed by visual assessment. Visual assessment has limited accuracy compared to fractional flow reserve and quantitative coronary angiography, which are more time-consumin...
Coronary Vessels
Coronary Stenosis
Fractional Flow Reserve, Myocardial
Male
Middle Aged
Severity of Illness Index
Deep Learning
Retrospective Studies
Female
Reproducibility of Results
Aged
Predictive Value of Tests
Coronary Angiography
Radiographic Image Interpretation, Computer-Assisted
Coronary Artery Disease
Humans
Automation
Multimodal deep learning for predicting in-hospital mortality in heart failure patients using longitudinal chest X-rays and electronic health records.
The international journal of cardiovascular imaging
Jan 9, 2025
Amid an aging global population, heart failure has become a leading cause of hospitalization among older people. Its high prevalence and mortality rates underscore the importance of accurate mortality prediction for swift disease progression assessme...
Electronic Health Records
Female
Reproducibility of Results
Risk Factors
Aged
Humans
Decision Support Techniques
Prognosis
Feasibility Studies
Heart Failure
Radiography, Thoracic
Deep Learning
Time Factors
Hospital Mortality
Predictive Value of Tests
Aged, 80 and over
Male
Middle Aged
Risk Assessment
Prediction of Aneurysm Sac Shrinkage After Endovascular Aortic Repair Using Machine Learning-Based Decision Tree Analysis.
The Journal of surgical research
Jan 9, 2025
INTRODUCTION: A simple risk stratification model to predict aneurysm sac shrinkagein patients undergoing endovascular aortic repair (EVAR) for abdominal aortic aneurysms (AAA) was developed using machine learning-based decision tree analysis.
Deep learning model for automatic detection of different types of microaneurysms in diabetic retinopathy.
Eye (London, England)
Jan 9, 2025
PURPOSE: This study aims to develop a deep-learning-based software capable of detecting and differentiating microaneurysms (MAs) as hyporeflective or hyperreflective on structural optical coherence tomography (OCT) images in patients with non-prolife...
Deep Learning-Based Segmentation of Cervical Posterior Longitudinal Ligament Ossification in Computed Tomography Images and Assessment of Spinal Cord Compression: A Two-Center Study.
World neurosurgery
Jan 9, 2025
OBJECTIVE: This study aims to develop a fully automated, computed tomography (CT)-based deep learning (DL) model to segment ossified lesions of the posterior longitudinal ligament and to measure the thickness of the ossified material and calculate th...
Investigating factors influencing quality of life in thyroid eye disease: insight from machine learning approaches.
European thyroid journal
Jan 9, 2025
AIMS: Thyroid eye disease (TED) is an autoimmune orbital disorder that diminishes the quality of life (QOL) in affected individuals. Graves' ophthalmopathy (GO)-QOL questionnaire effectively assesses TED's effect on patients. This study aims to inves...
Prediction of urinary tract infection using machine learning methods: a study for finding the most-informative variables.
BMC medical informatics and decision making
Jan 9, 2025
BACKGROUND: Urinary tract infection (UTI) is a frequent health-threatening condition. Early reliable diagnosis of UTI helps to prevent misuse or overuse of antibiotics and hence prevent antibiotic resistance. The gold standard for UTI diagnosis is ur...
Estimation of TP53 mutations for endometrial cancer based on diffusion-weighted imaging deep learning and radiomics features.
BMC cancer
Jan 9, 2025
OBJECTIVES: To construct a prediction model based on deep learning (DL) and radiomics features of diffusion weighted imaging (DWI), and clinical variables for evaluating TP53 mutations in endometrial cancer (EC).
Machine-learning-based cost prediction models for inpatients with mental disorders in China.
BMC psychiatry
Jan 9, 2025
BACKGROUND: Mental disorders are increasingly prevalent, leading to increased medical expenditures. To refine the reimbursement of medical costs for inpatients with mental disorders by health insurance, an accurate prediction model is essential. Per-...
Using XBGoost, an interpretable machine learning model, for diagnosing prostate cancer in patients with PSA < 20 ng/ml based on the PSAMR indicator.
Scientific reports
Jan 9, 2025
To create a diagnostic tool before biopsy for patients with prostate-specific antigen (PSA) levels < 20 ng/ml to minimize prostate biopsy-related discomfort and risks. Data from 655 patients who underwent transperineal prostate biopsy at the First Af...
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