AIMC Topic: Family Characteristics
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Machine learning based classification of catastrophic health expenditures: a cross-sectional study of Korean low-income households.
BMC health services research
Aug 7, 2025
BACKGROUND: Despite the National Health Insurance (NHI) system implemented in South Korea, concerns persist regarding access to health coverage for low-income households. To address this issue, this study aims to use machine learning-based data minin...
Understanding the determinants of treated bed net use in Ethiopia: A machine learning classification approach using PMA Ethiopia 2023 survey data.
PloS one
Jul 7, 2025
INTRODUCTION: Malaria remains a significant public health challenge in Ethiopia, with over 7.3 million cases and 1,157 deaths reported between January 1 and October 20, 2024. Despite extensive distribution campaigns, 35% of insecticide-treated nets (...
The impact of intelligent devices utilization on household medical expenditure of older adults in China.
Scientific reports
Jul 2, 2025
With the rapid development of artificial intelligence, there is an increasing utilization of intelligent devices by older adults. The relationship between the utilization of intelligent devices and household medical expenditure has garnered widesprea...
Efficiency-Driven Adaptive Task Planning for Household Robot Based on Hierarchical Item-Environment Cognition.
IEEE transactions on cybernetics
Mar 21, 2025
Task planning focused on household robots represents a conventional yet complex research domain, necessitating the development of task plans that enable robots to execute unfamiliar household services. This area has garnered significant research inte...
Assessing fecal contamination from human and environmental sources using as an indicator in rural eastern Ethiopian households-a cross-sectional study from the EXCAM project.
Frontiers in public health
Jan 6, 2025
INTRODUCTION: Enteric pathogens are a leading causes of diarrheal deaths in low-and middle-income countries. The Exposure Assessment of Infections in Rural Ethiopia (EXCAM) project, aims to identify potential sources of bacteria in the genus and, m...
Unveiling predictive factors for household-level stunting in India: A machine learning approach using NFHS-5 and satellite-driven data.
Nutrition (Burbank, Los Angeles County, Calif.)
Dec 24, 2024
OBJECTIVES: Childhood stunting remains a significant public health issue in India, affecting approximately 35% of children under 5. Despite extensive research, existing prediction models often fail to incorporate diverse data sources and address the ...
Determinants of adoption of household water treatment in Haiti using two analysis methods: logistic regression and machine learning.
Journal of water and health
Aug 21, 2024
Household water treatment (HWT) is recommended when safe drinking water is limited. To understand determinants of HWT adoption, we conducted a cross-sectional survey with 650 households across different regions in Haiti. Data were collected on 71 dem...
A GA-stacking ensemble approach for forecasting energy consumption in a smart household: A comparative study of ensemble methods.
Journal of environmental management
Jun 12, 2024
The considerable amount of energy utilized by buildings has led to various environmental challenges that adversely impact human existence. Predicting buildings' energy usage is commonly acknowledged as encouraging energy efficiency and enabling well-...
Tailoring Household Disaster Preparedness Interventions to Reduce Health Disparities: Nursing Implications from Machine Learning Importance Features from the 2018-2020 FEMA National Household Survey.
International journal of environmental research and public health
Apr 23, 2024
Tailored disaster preparedness interventions may be more effective and equitable, yet little is known about specific factors associated with disaster household preparedness for older adults and/or those with African American/Black identities. This st...
How Lazy Are Pet Cats Really? Using Machine Learning and Accelerometry to Get a Glimpse into the Behaviour of Privately Owned Cats in Different Households.
Sensors (Basel, Switzerland)
Apr 19, 2024
Surprisingly little is known about how the home environment influences the behaviour of pet cats. This study aimed to determine how factors in the home environment (e.g., with or without outdoor access, urban vs. rural, presence of a child) and the s...
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