Beau Norgeot
- Artificial Intelligence top 5%
- Health Informatics top 0.5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Health Information Management top 2%
- Rheumatology
- Co-authors
- Atul J. ButteBenjamin S. GlicksbergMilena GianfrancescoBin YuRaquel DiasSuchi SariaAli TorkamaniBrett K. Beaulieu‐Jones
- Topics
- Machine Learning in Healthcare (10 papers)Advanced Causal Inference Techniques (5 papers)Health Systems, Economic Evaluations, Quality of Life (3 papers)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Beau Norgeot
16 papers receiving 746 citations
Peers
Comparison fields: 5 of 117
- Artificial Intelligence 300
- Health Informatics 215
- Radiology, Nuclear Medicine and Imaging 186
- Health Information Management 91
- Rheumatology 80
Countries citing papers authored by Beau Norgeot
This map shows the geographic impact of Beau Norgeot'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 Beau Norgeot with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Beau Norgeot more than expected).
Fields of papers citing papers by Beau Norgeot
This network shows the impact of papers produced by Beau Norgeot. 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 Beau Norgeot. The network helps show where Beau Norgeot may publish in the future.
Co-authorship network of co-authors of Beau Norgeot
This figure shows the co-authorship network connecting the top 25 collaborators of Beau Norgeot. A scholar is included among the top collaborators of Beau Norgeot based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Beau Norgeot. Beau Norgeot is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 0 | |
| 3 | 16 | |
| 4 | 4 | |
| 5 | 3 | |
| 6 | 13 | |
| 7 | 8 | |
| 8 | 13 | |
| 9 | 3 | |
| 10 | 10 | |
| 11 | MAgEC: Using Non-Homogeneous Ensemble Consensus for Predicting Drivers in Unexpected Mechanical Ventilation. | 1 |
| 12 | 61 | |
| 13 | 322 | |
| 14 | DEEP LEARNING IN PERSONALIZED MEDICINE: APPLICATIONS IN PATIENT SIMILARITY, PROGNOSIS, AND OPTIMAL TREATMENT SELECTION | 1 |
| 15 | 145 | |
| 16 | 152 | |
| 17 | 3 |
About Beau Norgeot
Beau Norgeot is a scholar working on Health Informatics, Statistics and Probability and Health Information Management, having authored 17 papers that have together received 762 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (10 papers), Advanced Causal Inference Techniques (5 papers) and Health Systems, Economic Evaluations, Quality of Life (3 papers). The work is most often cited by research in Health Informatics (215 citations), Health Information Management (91 citations) and Artificial Intelligence (300 citations). Beau Norgeot has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Atul J. Butte, Benjamin S. Glicksberg, Milena Gianfrancesco, Bin Yu, Raquel Dias, Suchi Saria, Ali Torkamani, Brett K. Beaulieu‐Jones, Giorgio Quer and Isaac S. Kohane. Their work appears in journals such as Nature Medicine, Nature Communications and Journal of Medical Internet Research.
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.