Predicting Children's Myopia Risk : A Monte Carlo Approach to Compare the Performance of Machine Learning Models
Artiemjew, P., Cybulski, R., Emamian, M., Grzybowski, A., Jankowski, A., Lanca, C., Mehravaran, S., Młyński, M., Morawski, C., Nordhausen, K., Pärssinen, O., & Ropiak, K. (2024). Predicting Children's Myopia Risk : A Monte Carlo Approach to Compare the Performance of Machine Learning Models. In A. P. Rocha, L. Steels, & J. V. D. Herik (Eds.), ICAART 2024 : Proceedings of the 16th International Conference on Agents and Artificial Intelligence, Volume 3 (pp. 1092-1099). SCITEPRESS Science and Technology Publications. https://doi.org/10.5220/0012435500003636
Authors
Date
2024Copyright
© 2024 SCITEPRESS
This study presents the initial results of the Myopia Risk Calculator (MRC) Consortium, introducing an innovative approach to predict myopia risk by using trustworthy machine-learning models. The dataset included approximately 7,945 records (eyes) from 3,989 children. We developed a myopia risk calculator and an accompanying web interface. Central to our research is the challenge of model trustworthiness, specifically evaluating the effectiveness and robustness of AI (Artificial Intelligence)/ML (Machine Learning)/NLP (Natural Language Processing) models. We adopted a robust methodology combining Monte Carlo simulations with cross-validation techniques to assess model performance. Our experiments revealed that an ensemble of classifiers and regression models with Lasso regression techniques provided the best outcomes for predicting myopia risk. Future research aims to enhance model accuracy by integrating image and synthetic data, including advanced Monte Carlo simulations.
Publisher
SCITEPRESS Science and Technology PublicationsParent publication ISBN
978-989-758-680-4Conference
International Conference on Agents and Artificial IntelligenceIs part of publication
ICAART 2024 : Proceedings of the 16th International Conference on Agents and Artificial Intelligence, Volume 3ISSN Search the Publication Forum
2184-433XKeywords
Publication in research information system
https://converis.jyu.fi/converis/portal/detail/Publication/207561430
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Additional information about funding
Shahroud School Children Eye Cohort Study is funded by the Noor Ophthalmology Research Center and Shahroud University of Medical Sciences. (Grant numbers: 9329, 960351).License
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