David A. Fisher
- Surgery top 5%
- Orthopaedic implants and arthroplasty 21
- Total Knee Arthroplasty Outcomes 19
- Orthopedic Infections and Treatments 13
- Orthopedic Surgery and Rehabilitation 7
- Knee injuries and reconstruction techniques 4
- Dermatology top 5%
- Artificial Intelligence top 5%
- Topic Modeling 8
- Natural Language Processing Techniques 8
- Orthopedics and Sports Medicine top 10%
- Rheumatology top 10%
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- Autoimmune Bullous Skin Diseases 3
- Co-authors
- Melanie WattsKenneth DavisEllen RiloffBrian D. DierckmanClaire CardieDavid F. DaluryStephen SoderlandWendy G. Lehnert
- Journals
- The Journal of Arthroplasty (11 papers)Orthopedics (5 papers)Journal of the American Academy of Dermatology (3 papers)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
David A. Fisher
68 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 153
- Surgery 891
- Dermatology 133
- Artificial Intelligence 327
- Orthopedics and Sports Medicine 86
- Rheumatology 120
Countries citing papers authored by David A. Fisher
This map shows the geographic impact of David A. Fisher'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 David A. Fisher with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David A. Fisher more than expected).
Fields of papers citing papers by David A. Fisher
This network shows the impact of papers produced by David A. Fisher. 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 David A. Fisher. The network helps show where David A. Fisher may publish in the future.
Co-authorship network
The 25 scholars most cited alongside David A. Fisher, 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 | 2014 | 80 | |
| 2 | 2013 | 14 | |
| 3 | 2013 | 13 | |
| 4 | 2011 | 66 | |
| 5 | 2011 | 16 | |
| 6 | 2007 | 186 | |
| 7 | 2007 | 27 | |
| 8 | 2005 | 1 | |
| 9 | 2003 | 93 | |
| 10 | INQUERY and TREC-9. | 2000 | 66 |
| 11 | 2000 | 8 | |
| 12 | 2000 | 5 | |
| 13 | 2000 | 7 | |
| 14 | 1998 | 3 | |
| 15 | 1998 | 24 | |
| 16 | 1997 | 39 | |
| 17 | 1996 | 6 | |
| 18 | Machine Learning of Text Analysis Rules for Clinical Records | 1995 | 13 |
| 19 | 1994 | 43 | |
| 20 | 1991 | 6 |
About David A. Fisher
David A. Fisher is a scholar working on Dermatology, Surgery, Rheumatology, Artificial Intelligence and Rehabilitation, having authored 70 papers that have together received 1.8k indexed citations. Recurring topics across this work include Orthopaedic implants and arthroplasty (21 papers), Total Knee Arthroplasty Outcomes (19 papers), Orthopedic Infections and Treatments (13 papers), Topic Modeling (8 papers), Natural Language Processing Techniques (8 papers), Orthopedic Surgery and Rehabilitation (7 papers), Knee injuries and reconstruction techniques (4 papers) and Autoimmune Bullous Skin Diseases (3 papers). The work is most often cited by research in Surgery (891 citations), Dermatology (133 citations), Artificial Intelligence (327 citations), Orthopedics and Sports Medicine (86 citations) and Rheumatology (120 citations). David A. Fisher has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Melanie Watts, Kenneth Davis, Ellen Riloff, Brian D. Dierckman, Claire Cardie, David F. Dalury, Stephen Soderland, Wendy G. Lehnert, Mary Jo Adams and Fangfang Feng. Their work appears in journals such as The Journal of Arthroplasty, Orthopedics, Journal of the American Academy of Dermatology, The American Journal of Sports Medicine and Clinical Orthopaedics and Related 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.