Su-In Lee

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 20

Top Topics

Acute Myeloid Leukemia

Machine Learning

Top Venues

Nature medicine

Nature biomedical engineering

Nature communications

This page only lists publications with an associated author ORCID identifier.

Publications

Chanwoo Kim, Soham U Gadgil, Alex J DeGrave, Jesutofunmi A Omiye, Zhuo Ran Cai, Roxana Daneshjou, Su-In Lee
Transparent medical image AI via an image-text foundation model grounded in medical literature. Nature medicine 30 (4) (2024)
Chanwoo Kim, Soham U Gadgil, Alex J DeGrave, Jesutofunmi A Omiye, Zhuo Ran Cai, Roxana Daneshjou, Su-In Lee
Transparent medical image AI via an image-text foundation model grounded in medical literature. Nature medicine 30 (4) (2024)
Chanwoo Kim, Soham U Gadgil, Alex J DeGrave, Jesutofunmi A Omiye, Zhuo Ran Cai, Roxana Daneshjou, Su-In Lee
Transparent medical image AI via an image-text foundation model grounded in medical literature. Nature medicine 30 (4) (2024)
Chanwoo Kim, Soham U Gadgil, Alex J DeGrave, Jesutofunmi A Omiye, Zhuo Ran Cai, Roxana Daneshjou, Su-In Lee
Transparent medical image AI via an image-text foundation model grounded in medical literature. Nature medicine 30 (4) (2024)
Chanwoo Kim, Soham U Gadgil, Alex J DeGrave, Jesutofunmi A Omiye, Zhuo Ran Cai, Roxana Daneshjou, Su-In Lee
Transparent medical image AI via an image-text foundation model grounded in medical literature. Nature medicine (2024)
Chanwoo Kim, Soham U Gadgil, Alex J DeGrave, Jesutofunmi A Omiye, Zhuo Ran Cai, Roxana Daneshjou, Su-In Lee
Transparent medical image AI via an image-text foundation model grounded in medical literature. Nature medicine 30 (4) (2024)
Joseph D Janizek, Ayse B Dincer, Safiye Celik, Hugh Chen, William Chen, Kamila Naxerova, Su-In Lee
Uncovering expression signatures of synergistic drug responses via ensembles of explainable machine-learning models. Nature biomedical engineering (2023)
Alex J DeGrave, Zhuo Ran Cai, Joseph D Janizek, Roxana Daneshjou, Su-In Lee
Auditing the inference processes of medical-image classifiers by leveraging generative AI and the expertise of physicians. Nature biomedical engineering (2023)
Chanwoo Kim, Soham U Gadgil, Alex J DeGrave, Zhuo Ran Cai, Roxana Daneshjou, Su-In Lee
Fostering transparent medical image AI via an image-text foundation model grounded in medical literature. medRxiv : the preprint server for health sciences (2023)
Ethan Weinberger, Chris Lin, Su-In Lee
Isolating salient variations of interest in single-cell data with contrastiveVI. Nature methods (2023)
Ian Covert, Rohan Gala, Tim Wang, Karel Svoboda, Uygar Sümbül, Su-In Lee
Predictive and robust gene selection for spatial transcriptomics. Nature communications 14 (1) (2023)
Alex J DeGrave, Zhuo Ran Cai, Joseph D Janizek, Roxana Daneshjou, Su-In Lee
Dissection of medical AI reasoning processes via physician and generative-AI collaboration. medRxiv : the preprint server for health sciences (2023)
Gabriel Erion, Joseph D Janizek, Carly Hudelson, Richard B Utarnachitt, Andrew M McCoy, Michael R Sayre, Nathan J White, Su-In Lee
A cost-aware framework for the development of AI models for healthcare applications. Nature biomedical engineering (2022)
Hugh Chen, Scott M Lundberg, Su-In Lee
Explaining a series of models by propagating Shapley values. Nature communications 13 (1) (2022)
Benjamin J Heil, Michael M Hoffman, Florian Markowetz, Su-In Lee, Casey S Greene, Stephanie C Hicks
Reproducibility standards for machine learning in the life sciences. Nature methods 18 (10) (2021)
Hugh Chen, Scott M Lundberg, Gabriel Erion, Jerry H Kim, Su-In Lee
Forecasting adverse surgical events using self-supervised transfer learning for physiological signals. NPJ digital medicine 4 (1) (2021)
Alex J DeGrave, Joseph D Janizek, Su-In Lee
Course Corrections for Clinical AI. Kidney360 2 (12) (2021)
Nicasia Beebe-Wang, Safiye Celik, Ethan Weinberger, Pascal Sturmfels, Philip Lawrence De Jager, Sara Mostafavi, Su-In Lee
Unified AI framework to uncover deep interrelationships between gene expression and Alzheimer's disease neuropathologies. Nature communications 12 (1) (2021)
Su-In Lee, Safiye Celik, Benjamin A Logsdon, Scott M Lundberg, Timothy J Martins, Vivian G Oehler, Elihu H Estey, Chris P Miller, Sylvia Chien, Jin Dai, Akanksha Saxena, C Anthony Blau, Pamela S Becker
A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia. Nature communications 9 (1) (2018)
Scott M Lundberg, Bala Nair, Monica S Vavilala, Mayumi Horibe, Michael J Eisses, Trevor Adams, David E Liston, Daniel King-Wai Low, Shu-Fang Newman, Jerry Kim, Su-In Lee
Explainable machine-learning predictions for the prevention of hypoxaemia during surgery. Nature biomedical engineering 2 (10) (2018)