G. William Moore
Impact in
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- Artificial Intelligence in Healthcare
- Health Informatics top 10%
Papers in
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- AI in cancer detection 4
- Topic Modeling 2
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- Biomedical Text Mining and Ontologies 4
- Co-authors
- Krzysztof J. Cios (1 shared paper)Jules J. Berman (6 shared papers)Grover M. Hutchins (2 shared papers)Robert E. Miller (2 shared papers)Alan F. Scott (1 shared paper)Randy Hanzlick (1 shared paper)John J. Buchino (1 shared paper)Nina W. Matheson (1 shared paper)
- Journals
- Cancer Letters (1 paper)Artificial Intelligence in Medicine (1 paper)American Journal of Clinical Pathology (1 paper)Electronics and Power (2 papers)PubMed (4 papers)
- Partner nations
- United States
In The Last Decade
G. William Moore
11 papers receiving 417 citations
Peers
Comparison fields: 5 of 98
- Health Information Management 128
- Health Informatics 11
- Artificial Intelligence 206
- Information Systems 97
- Management Science and Operations Research 27
Countries citing papers authored by G. William Moore
This map shows the geographic impact of G. William Moore'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 G. William Moore with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G. William Moore more than expected).
Fields of papers citing papers by G. William Moore
This network shows the impact of papers produced by G. William Moore. 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 G. William Moore. The network helps show where G. William Moore may publish in the future.
Co-authors
The 12 scholars most cited alongside G. William Moore, 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 | 2002 | 396 | |
| 2 | SNOMED-encoded surgical pathology databases: a tool for epidemiologic investigation. | 1996 | 16 |
| 3 | 1994 | 15 | |
| 4 | Automatic SNOMED coding. | 1994 | 15 |
| 5 | Barrier word method for detecting molecular biology multiple word terms | 1988 | 9 |
| 6 | A prototype Internet autopsy database. 1625 consecutive fetal and neonatal autopsy facesheets spanning 20 years. | 1996 | 8 |
| 7 | 1994 | 7 | |
| 8 | 1987 | 5 | |
| 9 | A SNOMED analysis of three years' accessioned cases (40,124) of a surgical pathology department: implications for pathology-based demographic studies. | 1994 | 3 |
| 10 | 1986 | 1 | |
| 11 | 1987 | 1 |
About G. William Moore
G. William Moore is a scholar working on Artificial Intelligence, Molecular Biology, Health Information Management, Radiology, Nuclear Medicine and Imaging and Information Systems, having authored 11 papers that have together received 476 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (4 papers), AI in cancer detection (4 papers), Medical Coding and Health Information (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Topic Modeling (2 papers), Artificial Intelligence in Healthcare (1 paper), Autopsy Techniques and Outcomes (1 paper) and Pancreatic and Hepatic Oncology Research (1 paper). The work is most often cited by research in Health Information Management (128 citations), Health Informatics (11 citations), Artificial Intelligence (206 citations), Information Systems (97 citations) and Management Science and Operations Research (27 citations). G. William Moore has collaborated with scholars based in United States. Frequent co-authors include Krzysztof J. Cios, Jules J. Berman, Grover M. Hutchins, Robert E. Miller, Alan F. Scott, Randy Hanzlick, John J. Buchino, Nina W. Matheson, Kasper W. F. Tersmette and John K. Boitnott. Their work appears in journals such as Cancer Letters, Artificial Intelligence in Medicine, American Journal of Clinical Pathology, Electronics and Power and PubMed.
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.