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Andrew A. S. Soltan
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2020 – today
- 2024
- [j8]Jenny Yang, Hagen Triendl, Andrew A. S. Soltan
, Mangal Prakash, David A. Clifton:
Addressing label noise for electronic health records: insights from computer vision for tabular data. BMC Medical Informatics Decis. Mak. 24(1): 183 (2024) - [j7]Jenny Yang
Deep reinforcement learning for multi-class imbalanced training: applications in healthcare. Mach. Learn. 113(5): 2655-2674 (2024) - [j6]Anshul Thakur
Knowledge abstraction and filtering based federated learning over heterogeneous data views in healthcare. npj Digit. Medicine 7(1) (2024) - [c1]Soheila Molaei, Anshul Thakur, Ghazaleh Niknam, Andrew A. S. Soltan, Hadi Zare, David A. Clifton:
Federated Learning For Heterogeneous Electronic Health Records Utilising Augmented Temporal Graph Attention Networks. AISTATS 2024: 1342-1350 - 2023
- [j5]Jenny Yang
Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning. Nat. Mac. Intell. 5(8): 884-894 (2023) - [j4]Jenny Yang
An adversarial training framework for mitigating algorithmic biases in clinical machine learning. npj Digit. Medicine 6 (2023) - [j3]Omid Rohanian
Privacy-Aware Early Detection of COVID-19 Through Adversarial Training. IEEE J. Biomed. Health Informatics 27(3): 1249-1258 (2023) - 2022
- [j2]Jenny Yang
Machine learning generalizability across healthcare settings: insights from multi-site COVID-19 screening. npj Digit. Medicine 5 (2022) - [i2]Omid Rohanian, Samaneh Kouchaki, Andrew A. S. Soltan
Privacy-aware Early Detection of COVID-19 through Adversarial Training. CoRR abs/2201.03004 (2022) - [i1]Jenny Yang, Rasheed El-Bouri, Odhran O'Donoghue, Alexander S. Lachapelle, Andrew A. S. Soltan
Deep Reinforcement Learning for Multi-class Imbalanced Training. CoRR abs/2205.12070 (2022)
2010 – 2019
- 2017
- [j1]Andrew Thwaites
The difficult legacy of Turing's wager. J. Comput. Neurosci. 43(1): 1-4 (2017)
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last updated on 2024-12-10 20:44 CET by the dblp team
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