AIMC Topic: Middle Aged

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How do older adults react to social robots' offspring-like voices.

Social science & medicine (1982)
Social robots are being developed as a technological solution to alleviate older adults' loneliness due to separation from their offspring. This study explores how and why offspring-like voices affect older adults' acceptance of social robots from an...

Comprehensive prediction of outcomes in patients with ST elevation myocardial infarction (STEMI) using tree-based machine learning algorithms.

Computers in biology and medicine
ST elevation myocardial infarction (STEMI), a subtype of acute coronary syndrome, is one of the leading causes of morbidity and mortality. Revascularization using primary percutaneous coronary intervention (PPCI) is the gold standard treatment. Despi...

Noninvasive Total Cholesterol Level Measurement Using an E-Nose System and Machine Learning on Exhaled Breath Samples.

ACS sensors
In this paper, the first e-nose system coupled with machine learning algorithm for noninvasive measurement of total cholesterol level based on exhaled air sample was proposed. The study was conducted with the participation of 151 people, from whom a ...

Screening for severe coronary stenosis in patients with apparently normal electrocardiograms based on deep learning.

BMC medical informatics and decision making
BACKGROUND: Patients with severe coronary arterystenosis may present with apparently normal electrocardiograms (ECGs), making it difficult to detect adverse health conditions during routine screenings or physical examinations. Consequently, these pat...

Machine learning based predictive modeling and risk factors for prolonged SARS-CoV-2 shedding.

Journal of translational medicine
BACKGROUND: The global outbreak of the coronavirus disease 2019 (COVID-19) has been enormously damaging, in which prolonged shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, previously 2019-nCoV) infection is a challenge in the...

Establishing a machine learning dementia progression prediction model with multiple integrated data.

BMC medical research methodology
OBJECTIVE: Dementia is a significant medical and social issue in most developed countries. Practical tools for predicting the progression of degenerative dementia are highly valuable. Machine learning (ML) methods facilitate the construction of effec...

The development of an attention mechanism enhanced deep learning model and its application for body composition assessment with L3 CT images.

Scientific reports
Body composition assessment is very useful for evaluating a patient's status in the clinic, but recognizing, labeling, and calculating the body compositions would be burdensome. This study aims to develop a web-based service that could automate calcu...

Development and Validation of a Machine Learning-Based Early Warning Model for Lichenoid Vulvar Disease: Prediction Model Development Study.

Journal of medical Internet research
BACKGROUND: Given the complexity and diversity of lichenoid vulvar disease (LVD) risk factors, it is crucial to actively explore these factors and construct personalized warning models using relevant clinical variables to assess disease risk in patie...

Using Machine Learning to Predict the Duration of Atrial Fibrillation: Model Development and Validation.

JMIR medical informatics
BACKGROUND: Atrial fibrillation (AF) is a progressive disease, and its clinical type is classified according to the AF duration: paroxysmal AF, persistent AF (PeAF; AF duration of less than 1 year), and long-standing persistent AF (AF duration of mor...

Hospital Length of Stay Prediction for Planned Admissions Using Observational Medical Outcomes Partnership Common Data Model: Retrospective Study.

Journal of medical Internet research
BACKGROUND: Accurate hospital length of stay (LoS) prediction enables efficient resource management. Conventional LoS prediction models with limited covariates and nonstandardized data have limited reproducibility when applied to the general populati...