Alec B. Chapman

425 citations
21 papers · 173 · h-index 7

Impact in

    • Artificial Intelligence in Healthcare and Education
  • Toxicology top 10%
    • Pharmacovigilance and Adverse Drug Reactions

Papers in

Alec B. Chapman

18 papers receiving 163 citations

Peers

Alec B. Chapman
Comparison fields: 5 of 59
  • Health Informatics 13
  • Toxicology 19
  • Family Practice 5
  • Health Information Management 6
  • General Health Professions 30
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Countries citing papers authored by Alec B. Chapman

Since Specialization
Citations

This map shows the geographic impact of Alec B. Chapman'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 Alec B. Chapman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alec B. Chapman more than expected).

Fields of papers citing papers by Alec B. Chapman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alec B. Chapman. 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 Alec B. Chapman. The network helps show where Alec B. Chapman may publish in the future.

Co-authors

The 25 scholars most cited alongside Alec B. Chapman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Alec B. Chapman Line = papers co-authored together Alec B. Chapman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201957
2 202123
3
Detecting Evidence of Intra-abdominal Surgical Site Infections from Radiology Reports Using Natural Language Processing.
201919
4
A Natural Language Processing System for National COVID-19 Surveillance in the US Department of Veterans Affairs
202017
5 202410
6 20228
7 20217
8 20246
9 20225
10 20224
11
Hypertensive care and the small practice.
19894
12
Hybrid system for adverse drug event detection.
20184
13 20233
14 20242
15
A User-Friendly Interface for Concept Dictionary Expansion Using Word Embeddings and SNOMED-CT.
20181
16 20241
17 20241
18 20231
19 20210
20 20250

About Alec B. Chapman

Alec B. Chapman is a scholar working on General Health Professions, Epidemiology, Artificial Intelligence, Family Practice and Molecular Biology, having authored 21 papers that have together received 173 indexed citations. Recurring topics across this work include Homelessness and Social Issues (6 papers), Data-Driven Disease Surveillance (2 papers), Clinical Reasoning and Diagnostic Skills (2 papers), Machine Learning in Healthcare (2 papers), Housing, Finance, and Neoliberalism (1 paper), Cardiac, Anesthesia and Surgical Outcomes (1 paper), Flood Risk Assessment and Management (1 paper) and Pneumonia and Respiratory Infections (1 paper). The work is most often cited by research in Health Informatics (13 citations), Toxicology (19 citations), Family Practice (5 citations), Health Information Management (6 citations) and General Health Professions (30 citations). Alec B. Chapman has collaborated with scholars based in United States, Austria and Australia. Frequent co-authors include Kelly Peterson, Olga V. Patterson, Patrick R. Alba, Scott L. DuVall, Makoto Jones, Brian T. Bucher, Douglas S. Swords, Barbara Jones, Danielle L. Mowery and Wendy W. Chapman. Their work appears in journals such as Health Services Research, Journal of the American Medical Informatics Association, Journal of Biomedical Informatics, Evaluation and Program Planning and Academic Emergency 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.

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