William Boag
Impact in
- Health Informatics top 1%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 2%
- Topic Modeling
- Machine Learning in Healthcare
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
Papers in
-
- Topic Modeling 6
- Natural Language Processing Techniques 4
- Machine Learning in Healthcare 2
-
- Biomedical Text Mining and Ontologies 2
- Co-authors
- Matthew B. A. McDermott (2 shared papers)Wei‐Hung Weng (1 shared paper)Emily Alsentzer (1 shared paper)Tristan Naumann (2 shared papers)John R. Murphy (1 shared paper)Peter Szolovits (2 shared papers)Anna Rumshisky (4 shared papers)Catherine D’Ignazio (1 shared paper)
- Journals
- npj Digital Medicine (1 paper)Translational Psychiatry (1 paper)Text REtrieval Conference (1 paper)DSpace@MIT (Massachusetts Institute of Technology) (1 paper)
- Partner nations
- United StatesFinlandPakistan
In The Last Decade
William Boag
12 papers receiving 891 citations
William Boag's Hit Papers
Peers
Comparison fields: 5 of 86
- Health Informatics 87
- Artificial Intelligence 613
- Health Information Management 73
- Issues, ethics and legal aspects 7
- Molecular Biology 244
Countries citing papers authored by William Boag
This map shows the geographic impact of William Boag'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 William Boag with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William Boag more than expected).
Fields of papers citing papers by William Boag
This network shows the impact of papers produced by William Boag. 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 William Boag. The network helps show where William Boag may publish in the future.
Co-authors
The 25 scholars most cited alongside William Boag, 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 | Publicly Available Clinical Hit paper breakdown → | 2019 | 830 |
| 2 | 2023 | 22 | |
| 3 | 2021 | 21 | |
| 4 | 2022 | 18 | |
| 5 | Baselines for Chest X-Ray Report Generation | 2019 | 13 |
| 6 | 2024 | 7 | |
| 7 | 2015 | 5 | |
| 8 | 2016 | 4 | |
| 9 | Clinical Collabsheets: 53 Questions to Guide a Clinical Collaboration. | 2020 | 3 |
| 10 | A Hybrid Approach to Precision Medicine-related Biomedical Article Retrieval and Clinical Trial Matching. | 2017 | 2 |
| 11 | 2021 | 2 | |
| 12 | 2016 | 2 |
About William Boag
William Boag is a scholar working on Artificial Intelligence, Molecular Biology, Health Information Management, Computer Vision and Pattern Recognition and Health Informatics, having authored 12 papers that have together received 929 indexed citations. Recurring topics across this work include Topic Modeling (6 papers), Natural Language Processing Techniques (4 papers), Machine Learning in Healthcare (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), Biomedical Text Mining and Ontologies (2 papers), Multimodal Machine Learning Applications (2 papers), Neuroethics, Human Enhancement, Biomedical Innovations (1 paper) and Artificial Intelligence in Healthcare (1 paper). The work is most often cited by research in Health Informatics (87 citations), Artificial Intelligence (613 citations), Health Information Management (73 citations), Issues, ethics and legal aspects (7 citations) and Molecular Biology (244 citations). William Boag has collaborated with scholars based in United States, Finland and Pakistan. Frequent co-authors include Matthew B. A. McDermott, Wei‐Hung Weng, Emily Alsentzer, Tristan Naumann, John R. Murphy, Peter Szolovits, Anna Rumshisky, Catherine D’Ignazio, Harini Suresh and Roy H. Perlis. Their work appears in journals such as npj Digital Medicine, Translational Psychiatry, Text REtrieval Conference and DSpace@MIT (Massachusetts Institute of Technology).
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.