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
- Advanced Text Analysis Techniques 1
- Semantic Web and Ontologies 1
-
- Biomedical Text Mining and Ontologies 2
- Co-authors
- Matthew B. A. McDermott (2 shared papers)John R. Murphy (1 shared paper)Wei‐Hung Weng (1 shared paper)Tristan Naumann (2 shared papers)Emily Alsentzer (1 shared paper)Anna Rumshisky (4 shared papers)Peter Szolovits (2 shared papers)Catherine D’Ignazio (1 shared paper)
- Journals
- Translational Psychiatry (1 paper)npj Digital Medicine (1 paper)Text REtrieval Conference (1 paper)
- Partner nations
- United StatesUnited KingdomFinland
In The Last Decade
William Boag
12 papers receiving 836 citations
William Boag's Hit Papers
Peers
Comparison fields: 5 of 92
- Health Informatics 99
- Artificial Intelligence 715
- Health Information Management 93
- Issues, ethics and legal aspects 12
- Molecular Biology 301
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 | 781 |
| 2 | 2023 | 19 | |
| 3 | 2021 | 19 | |
| 4 | 2022 | 17 | |
| 5 | Baselines for Chest X-Ray Report Generation | 2019 | 13 |
| 6 | 2024 | 6 | |
| 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 | 2016 | 2 | |
| 12 | 2021 | 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 873 indexed citations. Recurring topics across this work include Topic Modeling (6 papers), Natural Language Processing Techniques (4 papers), Multimodal Machine Learning Applications (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), Biomedical Text Mining and Ontologies (2 papers), Machine Learning in Healthcare (2 papers), Advanced Text Analysis Techniques (1 paper) and Semantic Web and Ontologies (1 paper). The work is most often cited by research in Health Informatics (99 citations), Artificial Intelligence (715 citations), Health Information Management (93 citations), Issues, ethics and legal aspects (12 citations) and Molecular Biology (301 citations). William Boag has collaborated with scholars based in United States, United Kingdom and Finland. Frequent co-authors include Matthew B. A. McDermott, John R. Murphy, Wei‐Hung Weng, Tristan Naumann, Emily Alsentzer, Anna Rumshisky, Peter Szolovits, Catherine D’Ignazio, Harini Suresh and Thomas H. McCoy. Their work appears in journals such as Translational Psychiatry, npj Digital Medicine and Text REtrieval Conference.
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.