[HTML][HTML] Implications of Big Data Analytics, AI, Machine Learning, and Deep Learning in the Health Care System of Bangladesh: Scoping Review

MA Alam, MRUZ Sajib, F Rahman, S Ether… - Journal of Medical …, 2024 - jmir.org
Background The rapid advancement of digital technologies, particularly in big data analytics
(BDA), artificial intelligence (AI), machine learning (ML), and deep learning (DL), is …

Machine Learning Implementations in Childhood Stunting Research: A Systematic Literature Review

R Rahutomo, GN Elwirehardja, M Isnan… - 2023 International …, 2023 - ieeexplore.ieee.org
Childhood stunting is a condition anticipated to affect the growth potential of children under
the age of five. With numerous stunting researches that have been conducted, stunting …

Machine Learning Approach for Predicting the Impact of Food Insecurity on Nutrient Consumption and Malnutrition in Children Aged 6 Months to 5 Years

R Qasrawi, S Sgahir, M Nemer, M Halaikah… - Children, 2024 - mdpi.com
Background: Food insecurity significantly impacts children's health, affecting their
development across cognitive, physical, and socio-emotional dimensions. This study …

Analisis faktor ibu terhadap kejadian stunting pada balita usia 24-59 bulan di perkotaan

E Sugianti, A Buanasita… - AcTion: Aceh …, 2023 - ejournal.poltekkesaceh.ac.id
Prevalensi stunting pada balita masih tinggi di perkotaan. Faktor ibu seperti tinggi badan,
pendidikan, pekerjaan, kunjungan antenatal, dan status gizi sewaktu hamil menyebabkan …

[PDF][PDF] Prevalence and predictors of stunting in children under five years of age

S Rafique, S Afzal, H Amin, R Malik… - J Coll Physicians …, 2023 - researchgate.net
Stunting in children under five years of age is a significant health problem in many middle
and low-income countries worldwide. he study aimed to analyse the prevalence and …

[PDF][PDF] Pengaruh Intervensi Gizi Sensitif terhadap Kejadian Stunting pada Balita Usia 6-24 Bulan selama Pandemi Covid-19.

E Sugianti, BD Putri - Amerta Nutrition, 2022 - e-journal.unair.ac.id
ABSTRAK Latar Belakang: Stunting masih menjadi permasalahan nasional dan global
karena dampaknya terhadap kualitas generasi masa depan. Pemerintah sudah …

Unveiling Predictive Factors for Household-Level Stunting in India: A Machine Learning Approach Using NFHS-5 and Satellite-Driven Data

PK Arya, K Sur, T Kundu, S Dhote, SK Singh - Nutrition, 2024 - Elsevier
Childhood stunting remains a significant public health issue in India, affecting approximately
35% of children under five. Despite extensive research, existing prediction models often fail …

Feature selection and association rule learning identify risk factors of malnutrition among Ethiopian schoolchildren

WA Russel, J Perry, C Bonzani, A Dontino… - Frontiers in …, 2023 - frontiersin.org
Introduction Previous studies have sought to identify risk factors for malnutrition in
populations of schoolchildren, depending on traditional logistic regression methods …

Health and Socio-Demographic Risk Factors of Childhood Stunting: Assessing the Role of Factor Interactions Through the Development of an AI Predictive Model

T Hariguna, S Sarmini, A Azis - Journal of Applied Data Sciences, 2024 - bright-journal.org
Stunting is a significant global health problem, especially in developing countries such as
Indonesia. This study aims to develop and evaluate an artificial intelligence (AI)-based …

Parental sociodemographic factors associated with stunted children below 5 years of age in Kampar Indonesia

R Yefri, NI Lipoeto, AE Putra, M Kadim - Open Access Macedonian …, 2022 - oamjms.eu
BACKGROUND: The prevalence of stunted children under 5 years in Riau Province
exceeds 27.35% and Kampar District contributed the highest prevalence rate (32.05%) …