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Development and Validation of an Explainable Machine Learning Model to Assess the Prevalence Probability of Gastrointestinal Heat Retention Syndrome in Children: Cross-Sectional Study

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Published in:Journal of Medical Internet Research
Format: Online Article RSS Article
Published: 2026
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container_title Journal of Medical Internet Research
description
discipline_display Internal Medicine
discipline_facet Internal Medicine
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genre Journal Article
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institution FRELIP
journal_source_facet Journal of Medical Internet Research
last_indexed 2026-07-04T03:35:40.910Z
publishDate 2026
publishDateSort 2026
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spellingShingle Development and Validation of an Explainable Machine Learning Model to Assess the Prevalence Probability of Gastrointestinal Heat Retention Syndrome in Children: Cross-Sectional Study
Internal Medicine
General
Internal Medicine
sub_discipline_display General
sub_discipline_facet General
subject_display Internal Medicine
General
Internal Medicine
subject_facet Internal Medicine
General
Internal Medicine
title Development and Validation of an Explainable Machine Learning Model to Assess the Prevalence Probability of Gastrointestinal Heat Retention Syndrome in Children: Cross-Sectional Study
title_alt Desarrollo y validación de un modelo de aprendizaje automático explicable para evaluar la probabilidad de prevalencia del síndrome de retención de calor gastrointestinal en niños: Estudio transversal
Développement et validation d'un modèle d'apprentissage automatique explicable pour évaluer la probabilité de prévalence du syndrome de rétention de chaleur gastro-intestinale chez les enfants : Étude transversale
Desenvolvimento e Validação de um Modelo de Aprendizado de Máquina Explicável para Avaliar a Probabilidade de Prevalência da Síndrome de Retenção de Calor Gastrointestinal em Crianças: Estudo Transversal
title_auth Development and Validation of an Explainable Machine Learning Model to Assess the Prevalence Probability of Gastrointestinal Heat Retention Syndrome in Children: Cross-Sectional Study
title_es_txt Desarrollo y validación de un modelo de aprendizaje automático explicable para evaluar la probabilidad de prevalencia del síndrome de retención de calor gastrointestinal en niños: Estudio transversal
title_fr_txt Développement et validation d'un modèle d'apprentissage automatique explicable pour évaluer la probabilité de prévalence du syndrome de rétention de chaleur gastro-intestinale chez les enfants : Étude transversale
title_full Development and Validation of an Explainable Machine Learning Model to Assess the Prevalence Probability of Gastrointestinal Heat Retention Syndrome in Children: Cross-Sectional Study
title_fullStr Development and Validation of an Explainable Machine Learning Model to Assess the Prevalence Probability of Gastrointestinal Heat Retention Syndrome in Children: Cross-Sectional Study
title_full_unstemmed Development and Validation of an Explainable Machine Learning Model to Assess the Prevalence Probability of Gastrointestinal Heat Retention Syndrome in Children: Cross-Sectional Study
title_pt_txt Desenvolvimento e Validação de um Modelo de Aprendizado de Máquina Explicável para Avaliar a Probabilidade de Prevalência da Síndrome de Retenção de Calor Gastrointestinal em Crianças: Estudo Transversal
title_short Development and Validation of an Explainable Machine Learning Model to Assess the Prevalence Probability of Gastrointestinal Heat Retention Syndrome in Children: Cross-Sectional Study
title_sort development and validation of an explainable machine learning model to assess the prevalence probability of gastrointestinal heat retention syndrome in children: cross-sectional study
topic Internal Medicine
General
Internal Medicine
url https://www.jmir.org/2026/1/e94775