Jack W. Smith

2.9k total citations · 1 hit paper
78 papers, 1.8k citations indexed

About

Jack W. Smith is a scholar working on Artificial Intelligence, Molecular Biology and Health Information Management. According to data from OpenAlex, Jack W. Smith has authored 78 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Artificial Intelligence, 17 papers in Molecular Biology and 12 papers in Health Information Management. Recurrent topics in Jack W. Smith's work include Biomedical Text Mining and Ontologies (15 papers), Semantic Web and Ontologies (14 papers) and AI-based Problem Solving and Planning (11 papers). Jack W. Smith is often cited by papers focused on Biomedical Text Mining and Ontologies (15 papers), Semantic Web and Ontologies (14 papers) and AI-based Problem Solving and Planning (11 papers). Jack W. Smith collaborates with scholars based in United States, United Kingdom and Colombia. Jack W. Smith's co-authors include B. Chandrasekaran, R.S. Johannes, William C. Knowler, James E. Everhart, Todd R. Johnson, John R. Josephson, Elmer V. Bernstam, Michael C. Tanner, Edward H. Shortliffe and Philip J. Smith and has published in prestigious journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and Communications of the ACM.

In The Last Decade

Jack W. Smith

71 papers receiving 1.6k citations

Hit Papers

Using the ADAP Learning Algorithm to Forecast the Onset o... 1988 2026 2000 2013 1988 100 200 300 400

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jack W. Smith United States 17 874 351 207 183 133 78 1.8k
Feipei Lai Taiwan 30 774 0.9× 255 0.7× 240 1.2× 542 3.0× 202 1.5× 293 3.5k
Leila Shahmoradi Iran 23 511 0.6× 463 1.3× 101 0.5× 206 1.1× 195 1.5× 122 2.1k
Amar K. Das United States 25 968 1.1× 296 0.8× 662 3.2× 307 1.7× 238 1.8× 123 2.8k
Paul V. Biron United States 8 472 0.5× 411 1.2× 356 1.7× 184 1.0× 73 0.5× 10 1.3k
Illhoi Yoo United States 15 455 0.5× 290 0.8× 221 1.1× 292 1.6× 677 5.1× 42 1.9k
Klaus A. Kuhn Germany 29 534 0.6× 433 1.2× 318 1.5× 173 0.9× 159 1.2× 110 2.1k
Sooyoung Yoo South Korea 23 268 0.3× 317 0.9× 136 0.7× 137 0.7× 348 2.6× 127 1.8k
Peter Lucas Netherlands 28 1.2k 1.3× 244 0.7× 267 1.3× 208 1.1× 133 1.0× 202 2.5k
Mario Stefanelli Italy 31 1.0k 1.2× 711 2.0× 830 4.0× 251 1.4× 249 1.9× 122 3.2k
Farahnaz Sadoughi Iran 22 329 0.4× 516 1.5× 73 0.4× 195 1.1× 327 2.5× 136 1.8k

Countries citing papers authored by Jack W. Smith

Since Specialization
Citations

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

Fields of papers citing papers by Jack W. Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jack W. Smith. 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 Jack W. Smith. The network helps show where Jack W. Smith may publish in the future.

Co-authorship network of co-authors of Jack W. Smith

This figure shows the co-authorship network connecting the top 25 collaborators of Jack W. Smith. A scholar is included among the top collaborators of Jack W. Smith based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jack W. Smith. Jack W. Smith is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Smith, Jack W., A. LeBlanc, & William M. Wuest. (2025). From Natural Products to Small Molecules: Recent Advancements in Anti-MRSA Therapeutics. ACS Medicinal Chemistry Letters. 16(4). 542–551. 4 indexed citations
2.
Flórez-Arango, José F., et al.. (2019). SIM-CIG: A Serious Game to Practice and Improve Clinical Guidelines Adoption Based on Computer-Interpretable Guidelines. Studies in health technology and informatics. 264. 1997–1998. 3 indexed citations
3.
Smith, Jack W., et al.. (2018). EVALUATION OF SATISFACTION AND USABILITY OF A CLINICAL DECISION SUPPORT SYSTEM (CDSS) TARGETED FOR EARLY OBSTETRIC RISK ASSESSMENT AND PATIENT FOLLOW-UP. 3–11. 2 indexed citations
4.
Smith, Jack W.. (2012). The Anchorage, Alaska Veterans Court and Recidivism: July 6, 2004 – December 31, 2010. 29(1). 93–111. 14 indexed citations
5.
Herskovic, Jorge R, Trevor Cohen, Devika Subramanian, et al.. (2011). MEDRank: Using graph-based concept ranking to index biomedical texts. International Journal of Medical Informatics. 80(6). 431–441. 14 indexed citations
6.
Bernstam, Elmer V., Jack W. Smith, & Todd R. Johnson. (2009). What is biomedical informatics?. Journal of Biomedical Informatics. 43(1). 104–110. 73 indexed citations
7.
Jones, Bruce H., Steven H. Bullock, Bruce R. Burnham, et al.. (2009). A Process to Identify Military Injury Prevention Priorities Based on Injury Type and Limited Duty Days. American Journal of Preventive Medicine. 38(1). S19–S33. 97 indexed citations
8.
Wang, Hongbin, et al.. (2007). Probabilistic judgment on a coarser scale. Cognitive Systems Research. 9(3). 161–172. 2 indexed citations
9.
Wang, Hongbin, et al.. (2004). Probabilistic Judgment by a Coarser Scale: Behavioral and ERP Evidence. eScholarship (California Digital Library). 26(26). 2 indexed citations
10.
Walji, Muhammad F., et al.. (2004). Human-centered design of a distributed knowledge management system. Journal of Biomedical Informatics. 38(1). 4–17. 55 indexed citations
11.
Smith, Jack W., et al.. (2002). Implementing Medical Algorithms to Reduce Medical Errors.. PubMed Central. 1054–1054. 2 indexed citations
12.
Smith, Jack W., et al.. (2001). Automated Medical Algorithms: Issues for Medical Errors. Digital Commons-TMC (Texas Medical Center). 939–939. 1 indexed citations
13.
Simon, Sheldon R., et al.. (1999). Intelligent Support of Gait Analysis. Digital Commons-TMC (Texas Medical Center). 1090–1090. 2 indexed citations
14.
Smith, Jack W., et al.. (1988). Using the ADAP Learning Algorithm to Forecast the Onset of Diabetes Mellitus. PubMed Central. 261–265. 473 indexed citations breakdown →
15.
Chandrasekaran, Bharath & Jack W. Smith. (1985). Tenth Annual Workshop on Artificial Intelligence in Medicine: An Overview. AI Magazine. 6(2). 84–90. 1 indexed citations
16.
Speicher, Carl E. & Jack W. Smith. (1985). Helping Physicians Use Laboratory Tests. Clinics in Laboratory Medicine. 5(4). 653–663. 1 indexed citations
17.
Smith, Jack W.. (1984). Hospital building in the NHS. Things that go wrong.. BMJ. 289(6458). 1599–1602. 2 indexed citations
18.
Chandrasekaran, B., S. Mittal, & Jack W. Smith. (1981). MDX and related medical decision-making systems. International Joint Conference on Artificial Intelligence. 1055–1055. 1 indexed citations
19.
Mittal, S., B. Chandrasekaran, & Jack W. Smith. (1979). Overview of MDX-A System for Medical Diagnosis.. Europe PMC (PubMed Central). 34–46. 18 indexed citations
20.
Chandrasekaran, B., Fernando Gómez, S. Mittal, & Jack W. Smith. (1979). An approach to medical diagnosis based on conceptual structures. International Joint Conference on Artificial Intelligence. 134–142. 45 indexed citations

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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