AIMC Topic: Aged
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Case-control study combined with machine learning techniques to identify key genetic variations in GSK3B that affect susceptibility to diabetic kidney diseases.
BMC endocrine disorders
Jun 5, 2025
The role of genetic susceptibility in early warning and precise treatment of diabetic kidney disease (DKD) requires further investigation. A case-control study was conducted to evaluate the predictive effect of GSK3B genetic polymorphisms on the susc...
Multitask deep learning model based on multimodal data for predicting prognosis of rectal cancer: a multicenter retrospective study.
BMC medical informatics and decision making
Jun 5, 2025
BACKGROUND: Prognostic prediction is crucial to guide individual treatment for patients with rectal cancer. We aimed to develop and validated a multitask deep learning model for predicting prognosis in rectal cancer patients.
A systematic comparison of short-term and long-term mortality prediction in acute myocardial infarction using machine learning models.
BMC medical informatics and decision making
Jun 5, 2025
BACKGROUND AND OBJECTIVE: The machine learning (ML) models for acute myocardial infarction (AMI) are considered to have better predictive ability for mortality compared to conventional risk scoring models. However, previous ML prediction models have ...
A radiogenomics study on F-FDG PET/CT in endometrial cancer by a novel deep learning segmentation algorithm.
BMC cancer
Jun 5, 2025
OBJECTIVE: To create an automated PET/CT segmentation method and radiomics model to forecast Mismatch repair (MMR) and TP53 gene expression in endometrial cancer patients, and to examine the effect of gene expression variability on image texture feat...
Research on ischemic stroke risk assessment based on CTA radiomics and machine learning.
BMC medical imaging
Jun 5, 2025
BACKGROUND: The study explores the value of a model constructed by integrating CTA-based carotid plaque radiomic features, clinical risk factors, and plaque imaging characteristics for prognosticating the risk of ischemic stroke.
Predicting carbapenem-resistant Pseudomonas aeruginosa infection risk using XGBoost model and explainability.
Scientific reports
Jun 5, 2025
The prevalence and spread of carbapenem-resistant Pseudomonas aeruginosa (CRPA) is a global public health problem. This study aims to identify the risk factors of CRPA infection and construct a machine learning model to provide a prediction tool for ...
Epistasis regulates genetic control of cardiac hypertrophy.
Nature cardiovascular research
Jun 5, 2025
Although genetic variant effects often interact nonadditively, strategies to uncover epistasis remain in their infancy. Here we develop low-signal signed iterative random forests to elucidate the complex genetic architecture of cardiac hypertrophy, u...
Induced Pluripotent Stem Cells
Genome-Wide Association Study
Connectin
Gene Regulatory Networks
Humans
Genetic Predisposition to Disease
Female
Heart Failure
Phenotype
Aged
Magnetic Resonance Imaging
Ventricular Remodeling
Male
Receptor, IGF Type 1
Myocytes, Cardiac
Middle Aged
Hypertrophy, Left Ventricular
Deep Learning
Epistasis, Genetic
Machine learning-based prediction model for cognitive impairment risk in patients with chronic kidney disease.
PloS one
Jun 5, 2025
BACKGROUND: The high prevalence of cognitive impairment (CI) in Chronic kidney disease (CKD) patients impacts their quality of life and prognosis, yet risk prediction models for CI in this population remain underexplored.
AI-delirium guard: Predictive modeling of postoperative delirium in elderly surgical patients.
PloS one
Jun 5, 2025
INTRODUCTION: In older patients, postoperative delirium (POD) is a major complication that can result in greater morbidity, longer hospital stays, and higher healthcare expenses. Accurate prediction models for POD can enhance patient outcomes by guid...
Maximizing Lung Cancer Screening in High-Risk Population Leveraging ML-Developed Risk-Prediction Algorithms: Danish Retrospective Validation of LungFlag.
Clinical lung cancer
Jun 4, 2025
BACKGROUND: Early detection of lung cancer (LC) is crucial for curative treatment, but current screening methods face challenges due to high costs and poor adherence. Artificial intelligence tools, such as the LungFlag model, uses routine clinical da...
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