AIMC Topic: Health Status

Clear Filters Showing 11 to 20 of 127 articles

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
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...

The role of psychological factors in predicting self-rated health: implications from machine learning models.

Psychology, health & medicine
Self-rated health (SRH) is a significant predictor of future health outcomes. Despite the contribution of psychological factors in individuals' subjective health assessments, prior studies of machine learning-based prediction models primarily focused...

How do neighborhood environments impact adolescent health: a comprehensive study from subjective and objective perspectives using machine learning method.

Frontiers in public health
Existing studies have established a linear relationship between urban environments and adolescent health, but the combined impacts of subjective and objective environments on multi-dimensional health status (including physical and mental health) have...

Predicting host health status through an integrated machine learning framework: insights from healthy gut microbiome aging trajectory.

Scientific reports
The gut microbiome, recognized as a critical component in the development of chronic diseases and aging processes, constitutes a promising approach for predicting host health status. Previous research has underscored the potential of microbiome-based...

A Machine Learning Classification Model for Gastrointestinal Health in Cancer Survivors: Roles of Telomere Length and Social Determinants of Health.

International journal of environmental research and public health
BACKGROUND: Gastrointestinal (GI) distress is prevalent and often persistent among cancer survivors, impacting their quality of life, nutrition, daily function, and mortality. GI health screening is crucial for preventing and managing this distress. ...

Novel concept for the healthy population influencing factors.

Frontiers in public health
In the rapid urbanization process in China, due to reasons such as employment, education, and family reunification, the number of mobile population without registered residence in the local area has increased significantly. By 2020, the group had a p...

Applying machine learning to understand the role of social-emotional skills on subjective well-being and physical health.

Applied psychology. Health and well-being
Social-emotional skills are vital for individual development, yet research on which skills most effectively promote students' mental and physical health, particularly from a global perspective, remains limited. This study aims to address this gap by ...

Using machine learning to explore the predictors of life satisfaction trajectories in older adults.

Applied psychology. Health and well-being
Life satisfaction is vital for older adults' well-being, impacting various life aspects. It is dynamic, necessitating nuanced approaches to capture its trajectories accurately. This study aimed to explore the diverse trajectories and predictors of li...

Constructing prediction models and analyzing factors in suicidal ideation using machine learning, focusing on the older population.

PloS one
Suicide among the older population is a significant public health concern in South Korea. As the older individuals have long considered suicide before committing suicide trials, it is important to analyze the suicidal ideation that precedes the suici...

Predictive modeling for identification of older adults with high utilization of health and social services.

Scandinavian journal of primary health care
AIM: Machine learning techniques have demonstrated success in predictive modeling across various clinical cases. However, few studies have considered predicting the use of multisectoral health and social services among older adults. This research aim...