Lee, Su-In

A Unified Approach to Interpreting Model Predictions

Lundberg, S., & Lee, S.-I. (2017) · arXiv

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 23,707

From local explanations to global understanding with explainable AI for trees

Lundberg, S. M., Erion, G., Chen, H., DeGrave, A., Prutkin, J. M., Nair, B., Katz, R., Himmelfarb, J., Bansal, N., & Lee, S.-I. (2020) · Nature Machine Intelligence

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare

Cited by 10,551

Explainable machine-learning predictions for the prevention of hypoxaemia during surgery

Lundberg, S. M., Nair, B., Vavilala, M. S., Horibe, M., Eisses, M. J., Adams, T., Liston, D. E., Low, D. K.-W., Newman, S.-F., Kim, J., et al. (2018) · Nature Biomedical Engineering

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 1,967

Consistent Individualized Feature Attribution for Tree Ensembles

Lundberg, S. M., Erion, G. G., & Lee, S.-I. (2018) · arXiv

Explainable Artificial Intelligence (XAI)Data Mining Algorithms and Applications

Cited by 1,430

AI for radiographic COVID-19 detection selects shortcuts over signal

DeGrave, A. J., Janizek, J. D., & Lee, S.-I. (2021) · Nature Machine Intelligence

COVID-19 diagnosis using AIExplainable Artificial Intelligence (XAI)

Cited by 631

Massively parallel functional dissection of mammalian enhancers in vivo

Patwardhan, R. P., Hiatt, J. B., Witten, D. M., Kim, M. J., Smith, R. P., May, D., Lee, C., Andrie, J. M., Lee, S.-I., Cooper, G. M., et al. (2012) · Nature Biotechnology

Genomics and Chromatin DynamicsCRISPR and Genetic Engineering

Cited by 536

Learning generative models for protein fold families

Balakrishnan, S., Kamisetty, H., Carbonell, J. G., Lee, S., & Langmead, C. J. (2011) · Proteins: Structure, Function, and Bioinformatics

Protein Structure and DynamicsGenomics and Phylogenetic Studies

Cited by 316

Improving performance of deep learning models with axiomatic attribution priors and expected gradients

Erion, G., Janizek, J. D., Sturmfels, P., Lundberg, S. M., & Lee, S.-I. (2021) · Nature Machine Intelligence

Explainable Artificial Intelligence (XAI)Advanced Neural Network Applications

Cited by 300

Transparent medical image AI via an image–text foundation model grounded in medical literature

Kim, C., Gadgil, S. U., DeGrave, A. J., Omiye, J. A., Cai, Z. R., Daneshjou, R., & Lee, S.-I. (2024) · Nature Medicine

Artificial Intelligence in Healthcare and EducationExplainable Artificial Intelligence (XAI)

Cited by 125

Isolating salient variations of interest in single-cell data with contrastiveVI

Weinberger, E., Lin, C., & Lee, S.-I. (2023) · Nature Methods

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 66

Explainable machine learning predictions to help anesthesiologists prevent hypoxemia during surgery

Lundberg, S. M., Nair, B., Vavilala, M. S., Horibe, M., Eisses, M. J., Adams, T., Liston, D. E., Low, D. K.-W., Newman, S.-F., Kim, J., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory)

Machine Learning in HealthcareExplainable Artificial Intelligence (XAI)

Cited by 34