PhD in UCD School of Computer Science, University College Dublin 2018.9-2022.12
PhD thesis title: Explainable Clinical Decision Support for Complications in Pregnancy
Collaborated with UCD Perinatal Research Centre, School of Medicine
Publications:
Du, Y., Rafferty, A. R., McAuliffe, F.M., Mehegan, J. and Mooney, C. Towards an explainable clinical decision support system for large-for-gestational-age births. PLOS ONE (2023). DOI: 10.1371/journal.pone.0281821
Du, Y., Antoniadi, A. M., McNestry, C., McAuliffe, F. M., & Mooney, C. The Role of XAI in Advice-Taking from a Clinical Decision Support System: A Comparative User Study of Feature Contribution-Based and Example-Based Explanations. Applied Sciences (2022). DOI: 10.3390/app122010323
Du, Y., Rafferty, A. R., McAuliffe, F. M., Wei, L., and Mooney, C. An explainable machine learning-based clinical decision support system for prediction of gestational diabetes mellitus, Scientific Reports (2022). DOI: 10.1038/s41598-022-05112-2
Antoniadi, A.M., Du, Y., Guendouz, Y., Wei, L., Mazo, C., Becker, B.A. and Mooney, C. Current challenges and future opportunities for XAI in machine learning-based clinical decision support systems: a systematic review, Applied Sciences (2021). DOI: 10.3390/app11115088
Du, Y., Mehegan, J., McAuliffe, F.M. and Mooney, C. Prediction of Large for Gestational Age Infants in Overweight and Obese Women at Approximately 20 Gestational Weeks. The 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Virtual, Sep 21-24, 2020
Du Y. and Mooney, C. Prediction of Gestational Diabetes Mellitus in Overweight and Obese Caucasian Women using Machine Learning. AMIA 2021 Informatics Summit, Virtual, Mar 22 – 25, 2021
Du, Y., Rafferty, A.R., McAuliffe, F.M. and Mooney, C. Explaining large-for-gestational-age births: a random forest classifier with a novel local interpretation method. The 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, Virtual, Aug 1-4, 2021
Du Y. and Mooney, C. Early Prediction of Macrosomia using Machine Learning. The Grace Hopper Virtual Celebration 2021, Virtual, Sep 27 – Oct 1, 2021