AIMC Topic: Aged
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Explainable machine learning model for assessing health status in patients with comorbid coronary heart disease and depression: Development and validation study.
International journal of medical informatics
Jan 23, 2025
BACKGROUND: Coronary heart disease (CHD) and depression frequently co-occur, significantly impacting patient outcomes. However, comprehensive health status assessment tools for this complex population are lacking. This study aimed to develop and vali...
Application of elastic net for clinical outcome prediction and classification in progressive supranuclear palsy: A multicenter cohort study.
Parkinsonism & related disorders
Jan 23, 2025
BACKGROUND: Previous studies have used machine learning to identify clinically relevant atrophic regions in progressive supranuclear palsy (PSP). This study applied Elastic Net (EN) in PSP to uncover key atrophic patterns, offering a novel approach t...
Evaluation of a Machine Learning-Guided Strategy for Elevated Lipoprotein(a) Screening in Health Systems.
Circulation. Genomic and precision medicine
Jan 23, 2025
BACKGROUND: While universal screening for Lipoprotein(a) [Lp(a)] is increasingly recommended, <0.5% of patients undergo Lp(a) testing. Here, we assessed the feasibility of deploying Algorithmic Risk Inspection for Screening Elevated Lp(a) (ARISE), a ...
Random Survival Forest Machine Learning for the Prediction of Cardiovascular Events Among Patients With a Measured Lipoprotein(a) Level: A Model Development Study.
Circulation. Genomic and precision medicine
Jan 23, 2025
BACKGROUND: Established risk models may not be applicable to patients at higher cardiovascular risk with a measured Lp(a) (lipoprotein[a]) level, a causal risk factor for atherosclerotic cardiovascular disease.
Clinical validation of an individualized auto-adaptative serious game for combined cognitive and upper limb motor robotic rehabilitation after stroke.
Journal of neuroengineering and rehabilitation
Jan 23, 2025
BACKGROUND: Intensive rehabilitation through challenging and individualized tasks are recommended to enhance upper limb recovery after stroke. Robot-assisted therapy (RAT) and serious games could be used to enhance functional recovery by providing si...
Development and validation of a novel artificial intelligence algorithm for precise prediction the postoperative prognosis of esophageal squamous cell carcinoma.
BMC cancer
Jan 23, 2025
BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a highly aggressive malignancy, and current postoperative prognostic assessment methods remain unsatisfactory, underlining the urgent to develop a reliable approach for precision medicine. Give...
Enhanced detection of mild cognitive impairment in Alzheimer's disease: a hybrid model integrating dual biomarkers and advanced machine learning.
BMC geriatrics
Jan 23, 2025
Alzheimer's disease (AD) is a complex, progressive, and irreversible neurodegenerative disorder marked by cognitive decline and memory loss. Early diagnosis is the most effective strategy to slow the disease's progression. Mild Cognitive Impairment (...
Prognosis modelling of adverse events for post-PCI treated AMI patients based on inflammation and nutrition indexes.
BMC cardiovascular disorders
Jan 23, 2025
OBJECTIVE: This study aimed to evaluate the predictive performance of inflammatory and nutritional indices for adverse cardiovascular events (ACE) in patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI) using...
Aged
Male
Middle Aged
Nutrition Assessment
Biomarkers
Female
Risk Factors
Predictive Value of Tests
Percutaneous Coronary Intervention
Myocardial Infarction
Inflammation Mediators
Risk Assessment
Inflammation
Treatment Outcome
Decision Trees
Humans
Neural Networks, Computer
Machine Learning
Decision Support Techniques
Nutritional Status
A Novel Artificial Intelligence-Enhanced Digital Network for Prehospital Emergency Support: Community Intervention Study.
Journal of medical Internet research
Jan 23, 2025
BACKGROUND: Efficient emergency patient transport systems, which are crucial for delivering timely medical care to individuals in critical situations, face certain challenges. To address this, CONNECT-AI (CONnected Network for EMS Comprehensive Techn...
The role of CTGF and MFG-E8 in the prognosis assessment of SCAP: a study combining machine learning and nomogram analysis.
Frontiers in immunology
Jan 23, 2025
BACKGROUND: Severe Community-Acquired Pneumonia (SCAP) is a serious global health issue with high incidence and mortality rates. In recent years, the role of biomarkers such as Connective Tissue Growth Factor (CTGF) and Milk Fat Globule-Epidermal Gro...
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