Explainable deep learning in healthcare: A methodological survey from an attribution view D Jin, E Sergeeva, WH Weng, G Chauhan, P Szolovits WIREs Mechanisms of Disease 14 (3), e1548, 2022 | 47 | 2022 |
Cliner 2.0: Accessible and accurate clinical concept extraction W Boag, E Sergeeva, S Kulshreshtha, P Szolovits, A Rumshisky, ... arXiv preprint arXiv:1803.02245, 2018 | 38 | 2018 |
Negation scope detection in clinical notes and scientific abstracts: a feature-enriched LSTM-based approach E Sergeeva, H Zhu, P Prinsen, A Tahmasebi AMIA Summits on Translational Science Proceedings 2019, 212, 2019 | 19 | 2019 |
MIT-MEDG at SemEval-2018 task 7: Semantic relation classification via convolution neural network D Jin, F Dernoncourt, E Sergeeva, M McDermott, G Chauhan Proceedings of the 12th international workshop on semantic evaluation, 798-804, 2018 | 15 | 2018 |
Neural token representations and negation and speculation scope detection in biomedical and general domain text E Sergeeva, H Zhu, A Tahmasebi, P Szolovits Proceedings of the tenth international workshop on health text mining and …, 2019 | 14 | 2019 |
Right, No Matter Why: AI Fact-checking and AI Authority in Health-related Inquiry Settings E Sergeeva, A Sergeeva, H Tang, K Bongard-Blanchy, P Szolovits arXiv preprint arXiv:2310.14358, 2023 | | 2023 |
Explainable Deep Learning in Healthcare: A Methodological Survey from an Attribution View [Advanced Review] D Jin, E Sergeeva, WH Weng, G Chauhan, P Szolovits arXiv preprint arXiv:2112.02625, 2021 | | 2021 |