This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (3207) mHealth for Data Collection and Research (1192) Machine Learning (2066) Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health (86) Pregnancy Information, Education and Lifestyle Interventions (399)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69838, first published .
A Data-Driven Approach to Assessing Hepatitis B Mother-to-Child Transmission Risk Prediction Model: Machine Learning Perspective

A Data-Driven Approach to Assessing Hepatitis B Mother-to-Child Transmission Risk Prediction Model: Machine Learning Perspective

A Data-Driven Approach to Assessing Hepatitis B Mother-to-Child Transmission Risk Prediction Model: Machine Learning Perspective

Authors of this article:

Dung Nguyen Tien1 Author Orcid Image ;   Huong Thi Thu Bui1, 2 Author Orcid Image ;   Tram Hoang Thi Ngoc1 Author Orcid Image ;   Thuy Thi Pham1 Author Orcid Image ;   Dac Trung Nguyen1 Author Orcid Image ;   Huyen Nguyen Thi Thu1 Author Orcid Image ;   Thi Thu Hang Vu1 Author Orcid Image ;   Thi Lan Anh Luong3, 4 Author Orcid Image ;   Lan Thu Hoang3, 4 Author Orcid Image ;   Ho Cam Tu3, 5 Author Orcid Image ;   Nina Körber6 Author Orcid Image ;   Tanja Bauer6 Author Orcid Image ;   Lam Khanh Ho7 Author Orcid Image
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Journals

  1. Hoang T, Doan T, Hoang T, Ho C, Vu T, Nguyen T, Vu T, Dao T, Nguyen T, Nguyen P, Nguyen H, Vu C, Do P, Pham Q, Nguyen Q, Nguyen T, Ninh To T, Giang H, Luong T. Maximizing Diagnostic Yield in Intellectual Disability Through Exome Sequencing: Genotype–Phenotype Insights in a Vietnamese Cohort. Diagnostics 2025;15(22):2821 View