Michael Wornow
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
- Sensory Systems top 10%
- Hearing, Cochlea, Tinnitus, Genetics
Papers in
-
- Machine Learning in Healthcare 4
- Domain Adaptation and Few-Shot Learning 1
-
- RNA and protein synthesis mechanisms 2
- Ubiquitin and proteasome pathways 1
- Co-authors
- Nigam H. Shah (5 shared papers)Michael A. Pfeffer (3 shared papers)Jason Fries (3 shared papers)Ethan Steinberg (2 shared papers)Yizhe Xu (1 shared paper)Scott L. Fleming (1 shared paper)Birju Patel (1 shared paper)Rahul Thapa (1 shared paper)
- Journals
- Clinical Infectious Diseases (1 paper)JAMA (1 paper)PLoS Computational Biology (1 paper)Journal of Biomedical Informatics (1 paper)npj Digital Medicine (1 paper)
- Partner nations
- United StatesAustriaThailand
In The Last Decade
Michael Wornow
11 papers receiving 579 citations
Michael Wornow's Hit Papers
Peers
Comparison fields: 5 of 89
- Health Informatics 168
- Sensory Systems 41
- Health Information Management 34
- Family Practice 12
- Artificial Intelligence 130
Countries citing papers authored by Michael Wornow
This map shows the geographic impact of Michael Wornow'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 Michael Wornow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Wornow more than expected).
Fields of papers citing papers by Michael Wornow
This network shows the impact of papers produced by Michael Wornow. 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 Michael Wornow. The network helps show where Michael Wornow may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Wornow, 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 | Testing and Evaluation of Health Care Applications of Large Language Models Hit paper breakdown → | 2024 | 193 |
| 2 | 2023 | 159 | |
| 3 | 2020 | 142 | |
| 4 | 2024 | 23 | |
| 5 | 2024 | 22 | |
| 6 | 2022 | 16 | |
| 7 | 2023 | 13 | |
| 8 | 2022 | 5 | |
| 9 | 2020 | 5 | |
| 10 | 2024 | 4 | |
| 11 | Cut out the annotator, keep the cutout: better segmentation with weak supervision | 2021 | 3 |
| 12 | 2024 | 0 | |
| 13 | 2023 | 0 | |
| 14 | 2025 | 0 |
About Michael Wornow
Michael Wornow is a scholar working on Artificial Intelligence, Molecular Biology, Health Informatics, Management Information Systems and Health Information Management, having authored 14 papers that have together received 585 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (4 papers), Artificial Intelligence in Healthcare and Education (3 papers), Artificial Intelligence in Healthcare (2 papers), Business Process Modeling and Analysis (2 papers), RNA and protein synthesis mechanisms (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Ubiquitin and proteasome pathways (1 paper) and Domain Adaptation and Few-Shot Learning (1 paper). The work is most often cited by research in Health Informatics (168 citations), Sensory Systems (41 citations), Health Information Management (34 citations), Family Practice (12 citations) and Artificial Intelligence (130 citations). Michael Wornow has collaborated with scholars based in United States, Austria and Thailand. Frequent co-authors include Nigam H. Shah, Michael A. Pfeffer, Jason Fries, Ethan Steinberg, Yizhe Xu, Scott L. Fleming, Birju Patel, Rahul Thapa, Wei-Hsi Yeh and Jonathan C. Chen. Their work appears in journals such as Clinical Infectious Diseases, JAMA, PLoS Computational Biology, Journal of Biomedical Informatics and npj Digital Medicine.
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.