Secure and Private Vertical Federated Learning for Predicting Personalized CVA Outcomes
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-66538-7_18
Reference19 articles.
1. Allaart, C.G., Keyser, B., Bal, H., Van Halteren, A.: Vertical split learning-an exploration of predictive performance in medical and other use cases. In: 2022 International Joint Conference on Neural Networks (IJCNN), pp. 1–8. IEEE (2022)
2. Akiba, T., Sano, S., Yanase, T., Ohta, T., Koyama, M.: Optuna: a next-generation hyperparameter optimization framework. In: Proceedings of the 25th ACM SIGKDD International Conference, pp. 2623–2631 (2019)
3. Allaart, C.G., et al.: The meaning of a cva outcome prediction model for patients, family and health care providers: a qualitative evaluation. JMIR Preprints. 22/01/2024:56521 (2024)
4. Borsos, B., Allaart, C.G., van Halteren, A.: Predicting stroke outcome: a case for multimodal deep learning methods with tabular and ct perfusion data. Artif. Intell. Med. 147, 102719 (2024)
5. Ben-Israel, D., et al.: The impact of machine learning on patient care: a systematic review. Artif. Intell. Med. 103, 101785 (2020)
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