AIMC Topic: Health Surveys
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Predicting stunting status among under-5 children in Rwanda using neural network model: Evidence from 2020 Rwanda demographic and health survey.
F1000Research
Jan 20, 2025
BACKGROUND: Stunting is a serious public health concern in Rwanda, affecting around 33.3% of children under five in 2020. The researchers have employed machine learning algorithms to predict stunting in Rwanda; however, few studies used ANNs, despite...
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 ...
Unlocking insights: Using machine learning to identify wasting and risk factors in Egyptian children under 5.
Nutrition (Burbank, Los Angeles County, Calif.)
Nov 12, 2024
INTRODUCTION: Malnutrition, particularly wasting, continues to be a significant public health issue among children under five years in Egypt. Despite global advancements in child health, the prevalence of wasting remains a critical concern. This stud...
Predictive modeling and socioeconomic determinants of diarrhea in children under five in the Amhara Region, Ethiopia.
Frontiers in public health
Aug 1, 2024
BACKGROUND: Diarrheal disease, characterized by high morbidity and mortality rates, continues to be a serious public health concern, especially in developing nations such as Ethiopia. The significant burden it imposes on these countries underscores t...
Predicting long-term sleep deprivation using wearable sensors and health surveys.
Computers in biology and medicine
Jul 2, 2024
Sufficient sleep is essential for individual well-being. Inadequate sleep has been shown to have significant negative impacts on our attention, cognition, and mood. The measurement of sleep from in-bed physiological signals has progressed to where co...
Machine learning prediction of nutritional status among pregnant women in Bangladesh: Evidence from Bangladesh demographic and health survey 2017-18.
PloS one
May 31, 2024
AIM: Malnutrition in pregnant women significantly affects both mother and child health. This research aims to identify the best machine learning (ML) techniques for predicting the nutritional status of pregnant women in Bangladesh and detect the most...
Prediction of incomplete immunization among under-five children in East Africa from recent demographic and health surveys: a machine learning approach.
Scientific reports
May 21, 2024
The World Health Organization as part of the goal of universal vaccination coverage by 2030 for all individuals. The global under-five mortality rate declined from 59% in 1990 to 38% in 2019, due to high immunization coverage. Despite the significant...
Application of machine learning methods for predicting under-five mortality: analysis of Nigerian demographic health survey 2018 dataset.
BMC medical informatics and decision making
Mar 25, 2024
BACKGROUND: Under-five mortality remains a significant public health issue in developing countries. This study aimed to assess the effectiveness of various machine learning algorithms in predicting under-five mortality in Nigeria and identify the mos...
A Comparison of ChatGPT and Fine-Tuned Open Pre-Trained Transformers (OPT) Against Widely Used Sentiment Analysis Tools: Sentiment Analysis of COVID-19 Survey Data.
JMIR mental health
Jan 25, 2024
BACKGROUND: Health care providers and health-related researchers face significant challenges when applying sentiment analysis tools to health-related free-text survey data. Most state-of-the-art applications were developed in domains such as social m...
Exploring Differential Perceptions of Artificial Intelligence in Health Care Among Younger Versus Older Canadians: Results From the 2021 Canadian Digital Health Survey.
Journal of medical Internet research
Apr 28, 2023
BACKGROUND: The changing landscape of health care has led to the incorporation of powerful new technologies like artificial intelligence (AI) to assist with various services across a hospital. However, despite the potential outcomes that this tool ma...
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