Scott Lundberg
Impact in
- Health Informatics top 0.2%
- Artificial Intelligence in Healthcare and Education
- Health Information Management top 0.5%
- Artificial Intelligence in Healthcare
Papers in
-
- Explainable Artificial Intelligence (XAI) 8
- Machine Learning in Healthcare 5
- Machine Learning and Data Classification 5
- Topic Modeling 3
- Bayesian Modeling and Causal Inference 2
- Co-authors
- Su‐In LeeBala G. NairHugh ChenGabriel ErionJordan M. PrutkinRonit KatzJonathan HimmelfarbAlex J. DeGrave
- Journals
- Nature Communications (2 papers)Nature Machine Intelligence (2 papers)Academic Medicine (2 papers)Journal of Neurophysiology (1 paper)Discrete Applied Mathematics (1 paper)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Scott Lundberg
25 papers receiving 6.7k citations
Hit Papers
Peers
Comparison fields: 5 of 217
- Health Informatics 336
- Health Information Management 255
- Artificial Intelligence 1.7k
- Environmental Engineering 526
- Transportation 146
Countries citing papers authored by Scott Lundberg
This map shows the geographic impact of Scott Lundberg's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Scott Lundberg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Scott Lundberg more than expected).
Fields of papers citing papers by Scott Lundberg
This network shows the impact of papers produced by Scott Lundberg. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Scott Lundberg. The network helps show where Scott Lundberg may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Scott Lundberg, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Algorithms to estimate Shapley value feature attributions Hit paper breakdown → | 2023 | 199 |
| 2 | 2022 | 7 | |
| 3 | 2022 | 20 | |
| 4 | 2022 | 128 | |
| 5 | 2022 | 53 | |
| 6 | 2021 | 33 | |
| 7 | From local explanations to global understanding with explainable AI for trees Hit paper breakdown → | 2020 | 4764 |
| 8 | Understanding Global Feature Contributions With Additive Importance Measures | 2020 | 6 |
| 9 | 2020 | 15 | |
| 10 | 2019 | 7 | |
| 11 | Explainable machine-learning predictions for the prevention of hypoxaemia during surgery Hit paper breakdown → | 2018 | 1226 |
| 12 | 2017 | 192 | |
| 13 | 2017 | 8 | |
| 14 | 2016 | 22 | |
| 15 | 2010 | 2 | |
| 16 | 2010 | 2 | |
| 17 | 2010 | 9 | |
| 18 | 2010 | 3 | |
| 19 | 2006 | 20 | |
| 20 | 2006 | 27 |
About Scott Lundberg
Scott Lundberg is a scholar working on Health Informatics, Artificial Intelligence, Health Information Management, Emergency Medicine and Microbiology, having authored 25 papers that have together received 6.9k indexed citations. Recurring topics across this work include Explainable Artificial Intelligence (XAI) (8 papers), Machine Learning in Healthcare (5 papers), Machine Learning and Data Classification (5 papers), Topic Modeling (3 papers), Genomics and Chromatin Dynamics (3 papers), Bayesian Modeling and Causal Inference (2 papers), Software Engineering Research (2 papers) and Hospital Admissions and Outcomes (2 papers). The work is most often cited by research in Health Informatics (336 citations), Health Information Management (255 citations), Artificial Intelligence (1.7k citations), Environmental Engineering (526 citations) and Transportation (146 citations). Scott Lundberg has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Su‐In Lee, Bala G. Nair, Hugh Chen, Gabriel Erion, Jordan M. Prutkin, Ronit Katz, Jonathan Himmelfarb, Alex J. DeGrave, Nisha Bansal and David E. Liston. Their work appears in journals such as Nature Communications, Nature Machine Intelligence, Academic Medicine, Journal of Neurophysiology and Discrete Applied Mathematics.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.