| From local explanations to global understanding with explainable AI for trees SM Lundberg, G Erion, H Chen, A DeGrave, JM Prutkin, B Nair, R Katz, ... Nature machine intelligence 2 (1), 56-67, 2020 | 4224 | 2020 |
| True to the model or true to the data? H Chen, JD Janizek, S Lundberg, SI Lee arXiv preprint arXiv:2006.16234, 2020 | 151 | 2020 |
| Explaining models by propagating Shapley values of local components H Chen, S Lundberg, SI Lee Explainable AI in Healthcare and Medicine: Building a Culture of …, 2021 | 107 | 2021 |
| Algorithms to estimate Shapley value feature attributions H Chen, IC Covert, SM Lundberg, SI Lee Nature Machine Intelligence 5 (6), 590-601, 2023 | 79 | 2023 |
| Explaining a series of models by propagating local feature attributions H Chen, SM Lundberg, S Lee CoRR abs/2105.00108, 2021 | 66* | 2021 |
| Checkpoint ensembles: Ensemble methods from a single training process H Chen, S Lundberg, SI Lee arXiv preprint arXiv:1710.03282, 2017 | 64 | 2017 |
| Forecasting adverse surgical events using self-supervised transfer learning for physiological signals H Chen, SM Lundberg, G Erion, JH Kim, SI Lee NPJ Digital Medicine 4 (1), 167, 2021 | 36 | 2021 |
| Explainable AI for trees: From local explanations to global understanding. arXiv 2019 SM Lundberg, G Erion, H Chen, A DeGrave, JM Prutkin, B Nair, R Katz, ... arXiv preprint arXiv:1905.04610, 2020 | 30 | 2020 |
| Interpretable machine learning prediction of all-cause mortality W Qiu, H Chen, AB Dincer, S Lundberg, M Kaeberlein, SI Lee Communications Medicine 2 (1), 125, 2022 | 25 | 2022 |
| Hybrid gradient boosting trees and neural networks for forecasting operating room data H Chen, S Lundberg, SI Lee arXiv preprint arXiv:1801.07384, 2018 | 14 | 2018 |
| Probabilistic model-based approach for heart beat detection H Chen, Y Erol, E Shen, S Russell Physiological Measurement 37 (9), 1404, 2016 | 14 | 2016 |
| Uncovering expression signatures of synergistic drug responses via ensembles of explainable machine-learning models JD Janizek, AB Dincer, S Celik, H Chen, W Chen, K Naxerova, SI Lee Nature Biomedical Engineering 7 (6), 811-829, 2023 | 11 | 2023 |
| Contrastive corpus attribution for explaining representations C Lin, H Chen, C Kim, SI Lee The Eleventh International Conference on Learning Representations, 2022 | 7 | 2022 |
| Anesthesiologist-level forecasting of hypoxemia with only SpO2 data using deep learning G Erion, H Chen, SM Lundberg, SI Lee arXiv preprint arXiv:1712.00563, 2017 | 6 | 2017 |
| An explainable AI framework for interpretable biological age W Qiu, H Chen, M Kaeberlein, SI Lee medRxiv, 2022.10. 05.22280735, 2022 | 5 | 2022 |
| ExplaiNAble BioLogical Age (ENABL Age): an artificial intelligence framework for interpretable biological age W Qiu, H Chen, M Kaeberlein, SI Lee The Lancet Healthy Longevity 4 (12), e711-e723, 2023 | 4 | 2023 |
| Uncovering expression signatures of synergistic drug response using an ensemble of explainable AI models JD Janizek, AB Dincer, S Celik, H Chen, W Chen, K Naxerova, SI Lee BioRxiv, 2021.10. 06.463409, 2021 | 4 | 2021 |
| Physiological Signal Embeddings (PHASE) via Interpretable Stacked Models H Chen, S Lundberg, G Erion, SI Lee | | 2018 |
Su-In LeeComputer Science & Engineering, University of WashingtonVerified email at cs.washington.edu
