AIMC Topic: Aged
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Construction and validation of a machine learning-based prediction model for short-term mortality in critically ill patients with liver cirrhosis.
Clinics and research in hepatology and gastroenterology
Nov 30, 2024
OBJECTIVE: Critically ill patients with liver cirrhosis generally have a poor prognosis due to complications such as multiple organ failure. This study aims to develop a machine learning-based prediction model to forecast short-term mortality in crit...
Machine learning is better than surgeons at assessing unicompartmental knee replacement radiographs.
The Knee
Nov 30, 2024
BACKGROUND: Poor results occasionally occur after unicompartmental knee replacement (UKR). It is often difficult, even for experienced surgeons, to determine why patients have poor outcomes from radiographs. The aim was to compare the ability of expe...
Integrating Metabolomics Domain Knowledge with Explainable Machine Learning in Atherosclerotic Cardiovascular Disease Classification.
International journal of molecular sciences
Nov 30, 2024
Metabolomic data often present challenges due to high dimensionality, collinearity, and variability in metabolite concentrations. Machine learning (ML) application in metabolomic analyses is enabling the extraction of meaningful information from comp...
Impact of deep learning reconstruction on radiation dose reduction and cancer risk in CT examinations: a real-world clinical analysis.
European radiology
Nov 29, 2024
PURPOSE: The purpose of this study is to estimate the extent to which the implementation of deep learning reconstruction (DLR) may reduce the risk of radiation-induced cancer from CT examinations, utilizing real-world clinical data.
Development and Validation of a Machine Learning Radiomics Model based on Multiparametric MRI for Predicting Progesterone Receptor Expression in Meningioma: A Multicenter Study.
Academic radiology
Nov 29, 2024
RATIONALE AND OBJECTIVES: This study aimed to develop and validate a machine learning-based prediction model for preoperatively predicting progesterone receptor (PR) expression in meningioma patients using multiparametric magnetic resonance imaging (...
Interpretable time-series neural turing machine for prognostic prediction of patients with type 2 diabetes in physician-pharmacist collaborative clinics.
International journal of medical informatics
Nov 29, 2024
BACKGROUND: Type 2 diabetes (T2D) has become a serious health threat globally. However, the existing approaches for diabetes prediction mainly had difficulty in addressing multiple time-series features. This study aims to provide an adjunctive tool f...
MicroRNA signature for early prediction of knee osteoarthritis structural progression using integrated machine and deep learning approaches.
Osteoarthritis and cartilage
Nov 29, 2024
OBJECTIVE: Conventional methodologies are ineffective in predicting the rapid progression of knee osteoarthritis (OA). MicroRNAs (miRNAs) show promise as biomarkers for patient stratification. We aimed to develop a miRNA prognosis model for identifyi...
Assessment of clinical feasibility:offline adaptive radiotherapy for lung cancer utilizing kV iCBCT and UNet++ based deep learning model.
Journal of applied clinical medical physics
Nov 29, 2024
BACKGROUND: Lung cancer poses a significant global health challenge. Adaptive radiotherapy (ART) addresses uncertainties due to lung tumor dynamics. We aimed to investigate a comprehensively and systematically validated offline ART regimen with high ...
Left Atrial Wall Thickness Measured by a Machine Learning Method Predicts AF Recurrence After Pulmonary Vein Isolation.
Journal of cardiovascular electrophysiology
Nov 29, 2024
BACKGROUND: Left atrial (LA) remodeling plays a significant role in the progression of atrial fibrillation (AF). Although LA wall thickness (LAWT) has emerged as an indicator of structural remodeling, its impact on AF outcomes remains unclear. We aim...
Humans
Machine Learning
Retrospective Studies
Female
Atrial Function, Left
Pulmonary Veins
Atrial Remodeling
Predictive Value of Tests
Registries
Fibrosis
Atrial Fibrillation
Heart Atria
Heart Rate
Catheter Ablation
Recurrence
Risk Assessment
Time Factors
Treatment Outcome
Action Potentials
Risk Factors
Aged
Male
Middle Aged
An ECG-based machine-learning approach for mortality risk assessment in a large European population.
Journal of electrocardiology
Nov 29, 2024
AIMS: Through a simple machine learning approach, we aimed to assess the risk of all-cause mortality after 5 years in a European population, based on electrocardiogram (ECG) parameters, age, and sex.
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