Conference Paper2024Cited by 2

Using an Ensemble Machine Learning Model with Explainable AI (XAI) to Diagnose Gestational Diabetes Mellitus

S. T. Pasha, A. Islam, S. Sikder, M. T. Habib, M. Z. Alam, M. A. Amin

Diabetes Research and Clinical Practice (DRCP), 2024

Elsevier BV, Vol. 209, pp. 111504, ISBN: 0168-8227

  • Good Health and Well-being — Relevance: 94%
DOI: 10.1016/j.diabres.2024.111504URL

Keywords

  • gestational diabetes mellitus
  • Explainable AI
  • Ensemble learning
  • diagnosis

CCDS Authors

Prof. M Ashraful Amin, PhD
M Ashraful Amin, PhD

Prof. M Ashraful Amin, PhD

  • Founder Director, CCDS
  • Director, AI/ML, HCI & DS Wings

Professor

+1 more affiliation

Department of Information Sciences and Technology

George Mason University, USA

Published at

ACL, CHI, UbiComp, ECAI, WACV, PAKDD, IJCNN, ICPR, ICIP, HCII, CLEF, BLP, Scientific Reports, JMIR, IEEE Access, Smart Agricultural Technology, Frontiers in Computational Neuroscience, Diabetes Research and Clinical Practice, PLOS ONE

Research Interests

Machine Learning, Cognitive & Vision Science, Cybernetics, Surveillance & Security, ICT in Education, Health, & Agriculture, Human-Computer Interaction, Internet of Things, Robotics

Cited By

  1. 1.宁仪 白. (2024). Analysis of Specific Binding between TCR and Peptides Based on SVM Ensemble Learning. Advances in Applied Mathematics, 13(08), 3618–3624[10.12677/aam.2024.138344]
  2. 2.Desheng Li, Shang Shi, Mingli Zhang, Zhi Wen, Hao Zheng. (2026). Interpretable machine learning models for permafrost hydrothermal response to climatic variables. Cold Regions Science and Technology, 251, 105054[10.1016/j.coldregions.2026.105054]
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