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

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
  2. Wei Q, Song L, Song S, Zhang X, Qi X, Li K, Wang S, Liang Q. The blocking efficacy and safety of tenofovir disoproxil fumarate tablets on mother-to-child transmission in pregnant women with high serum HBV DNA load: a retrospective cohort study. BMC Pregnancy and Childbirth 2025 View