Accessibility settings

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

Formative Evaluation of Digital Health Interventions (3597) Mobile Health (mhealth) (3754) Apps, Mobile, Wearables for Diabetes (386) Machine Learning (2316) Diabetes Prevention (138) Artificial Intelligence (2469) Artificial Intelligence in Diabetes Care and Prevention (70)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50328, first published .
Plus-size woman in pink shirt smiling while looking at her smartphone on a couch.

A Mobile App That Addresses Interpretability Challenges in Machine Learning–Based Diabetes Predictions: Survey-Based User Study

A Mobile App That Addresses Interpretability Challenges in Machine Learning–Based Diabetes Predictions: Survey-Based User Study

Authors of this article:

Rasha Hendawi1 Author Orcid Image ;   Juan Li1 Author Orcid Image ;   Souradip Roy1 Author Orcid Image
Article Authors Cited by (13) Tweetations (2) Metrics

Journals

  1. Yousef H, Feng S, Jelinek H. Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers. Scientific Reports 2024;14(1) View
  2. Saarela M, Podgorelec V. Recent Applications of Explainable AI (XAI): A Systematic Literature Review. Applied Sciences 2024;14(19):8884 View
  3. Hasan R, Dattana V, Mahmood S, Hussain S. Towards Transparent Diabetes Prediction: Combining AutoML and Explainable AI for Improved Clinical Insights. Information 2024;16(1):7 View
  4. Tao Y, Hou J, Zhou G, Zhang D. Artificial intelligence applied to diabetes complications: a bibliometric analysis. Frontiers in Artificial Intelligence 2025;8 View
  5. Queipo-de-Llano E, Ciurcau M, Paz-Olalla A, Díaz-Agudo B, Recio-García J. eXplainable Artificial Intelligence for Hip Fracture Recognition. Applied Artificial Intelligence 2025;39(1) View
  6. Bauer J, Michalowski M. Human-centered explainability evaluation in clinical decision-making: a critical review of the literature. Journal of the American Medical Informatics Association 2025;32(9):1477 View
  7. Parab R, Feeley J, Valero M, Chadalawada L, Garcia G, Kar S, Madabhushi A, Breton M, Li J, Shao H, Pasquel F. Artificial Intelligence in Diabetes Care: Applications, Challenges, and Opportunities Ahead. Endocrine Practice 2025;31(12):1615 View
  8. Ghosh K, Chandra S, Ghosh S, Ghosh U. Artificial Intelligence in Personalized Medicine for Diabetes Mellitus: A Narrative Review. Cureus 2025 View
  9. Hameed Mousa A, Oday Alrubaye I, S. Kadhim M, Dheyaa Radhi A, M. Al-Slivani M, Mansoor Al-Amri R, Geok Pheng L. Diabetes at a Glance: Assessing AI Strategies for Early Diabetes Detection and Intervention via a Mobile App. Mesopotamian Journal of Computer Science 2025;2025:288 View
  10. Milbourn E, Lai J, Robinson D, Ackland D, Lee P. Wearable Technology and Machine Learning for Prediction of Performance-Based and Patient-Reported Outcome Measures: A Systematic Review. Sensors 2026;26(4):1218 View
  11. Joseph T, Dhaouadi A, Ramesh J, Sagahyroon A, Aloul F. Adapting EHR Foundational Models to Predict Diabetes Complications with Precision Explainability. Machine Learning and Knowledge Extraction 2026;8(4):89 View
  12. Yu S, Guan Z, Wang S, Mao H, Sheng B, Jia W, Li H. Artificial intelligence for diabetes complications: Detection, prediction, and clinical management. EngMedicine 2026;3(2):100133 View

Conference Proceedings

  1. Shiva Charan Reddy P, Vasista Somanath C, Basha S, Mahammad Eassa S, Kumar Reddy K. 2025 3rd International Conference on Sustainable Computing and Smart Systems (ICSCSS). Intelligent AI-Driven Framework for Precision-based Healthcare Diagnosis and Decision Support View