Thomas M. Gudewicz

487 total citations
14 papers, 343 citations indexed

About

Thomas M. Gudewicz is a scholar working on Molecular Biology, Neurology and Artificial Intelligence. According to data from OpenAlex, Thomas M. Gudewicz has authored 14 papers receiving a total of 343 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 3 papers in Neurology and 3 papers in Artificial Intelligence. Recurrent topics in Thomas M. Gudewicz's work include Biomedical Text Mining and Ontologies (3 papers), AI in cancer detection (3 papers) and Cancer and Skin Lesions (2 papers). Thomas M. Gudewicz is often cited by papers focused on Biomedical Text Mining and Ontologies (3 papers), AI in cancer detection (3 papers) and Cancer and Skin Lesions (2 papers). Thomas M. Gudewicz collaborates with scholars based in United States and France. Thomas M. Gudewicz's co-authors include Michelle C. Specht, Suzanne B. Coopey, Michele A. Gadd, Barbara L. Smith, Kevin S. Hughes, Judy E. Garber, Julliette M. Buckley, Fernanda Polubriaginof, Jiyeon Kim and Anand S. Dighe and has published in prestigious journals such as New England Journal of Medicine, Journal of Clinical Oncology and PLoS ONE.

In The Last Decade

Thomas M. Gudewicz

14 papers receiving 329 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Thomas M. Gudewicz United States	9	127	115	60	50	49	14	343
S Schulz Germany	14	153 1.2×	212 1.8×	27 0.5×	115 2.3×	9 0.2×	20	412
Ahmet Korkut Bellı Türkiye	9	73 0.6×	75 0.7×	42 0.7×	89 1.8×	103 2.1×	18	337
Sally J. O’Shea Ireland	12	65 0.5×	128 1.1×	78 1.3×	64 1.3×	221 4.5×	27	507
Liyan Xu United States	10	72 0.6×	59 0.5×	19 0.3×	24 0.5×	35 0.7×	29	414
Constance A. Roche United States	10	76 0.6×	92 0.8×	36 0.6×	140 2.8×	136 2.8×	16	435
Matthew Zhang United States	11	77 0.6×	99 0.9×	10 0.2×	39 0.8×	24 0.5×	37	488
Dominik Soll Germany	8	70 0.6×	59 0.5×	17 0.3×	14 0.3×	29 0.6×	16	349
Keita Koseki Japan	6	42 0.3×	101 0.9×	12 0.2×	50 1.0×	80 1.6×	11	410
Eric F. Glassy United States	9	164 1.3×	33 0.3×	7 0.1×	14 0.3×	48 1.0×	21	358
Margaret E. Williford United States	8	173 1.4×	47 0.4×	63 1.1×	130 2.6×	69 1.4×	12	415

Countries citing papers authored by Thomas M. Gudewicz

Since Specialization

Citations

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

Fields of papers citing papers by Thomas M. Gudewicz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas M. Gudewicz. 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 Thomas M. Gudewicz. The network helps show where Thomas M. Gudewicz may publish in the future.

Co-authorship network of co-authors of Thomas M. Gudewicz

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas M. Gudewicz. A scholar is included among the top collaborators of Thomas M. Gudewicz 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 Thomas M. Gudewicz. Thomas M. Gudewicz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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14 of 14 papers shown

Acevedo, Francisco, Rong Tang, Suzanne B. Coopey, et al.. (2018). Pathologic findings in reduction mammoplasty procedures identified by natural language processing of breast pathology reports: A surrogate for the population incidence of cancer and high risk lesions.. Journal of Clinical Oncology. 36(15_suppl). e13569–e13569. 1 indexed citations

Yanamadala, Vijay, Robert M. Koffie, Ganesh M. Shankar, et al.. (2016). Spinal cord glioblastoma: 25years of experience from a single institution. Journal of Clinical Neuroscience. 27. 138–141. 27 indexed citations

Yala, Adam, Regina Barzilay, Laura Salama, et al.. (2016). Using machine learning to parse breast pathology reports. Breast Cancer Research and Treatment. 161(2). 203–211. 72 indexed citations

Irwin, Kelly, Oliver Freudenreich, Jeffrey Peppercorn, et al.. (2016). Case 30-2016. New England Journal of Medicine. 375(13). 1270–1281. 6 indexed citations

Dang, Pragya A., et al.. (2016). Case 29-2016. New England Journal of Medicine. 375(12). 1172–1180. 4 indexed citations

Baron, Jason M., Bruce A. Beckwith, Anand S. Dighe, et al.. (2015). Environmental components and methods for engaging pathology residents in informatics training. Journal of Pathology Informatics. 6(1). 42–42. 3 indexed citations

Miller, Cynthia L., Anna Bettini, Frederick C. Koerner, et al.. (2014). Surgical excision of radial scars diagnosed by core biopsy may help predict future risk of breast cancer. Breast Cancer Research and Treatment. 145(2). 331–338. 30 indexed citations

King, Lindsay Y., Hui Zheng, Lan Wei, et al.. (2014). Host Genetics Predict Clinical Deterioration in HCV-Related Cirrhosis. PLoS ONE. 9(12). e114747–e114747. 12 indexed citations

Piris, Adriano, Yan Peng, Chakib Boussahmain, et al.. (2013). Cutaneous and mammary apocrine carcinomas have different immunoprofiles. Human Pathology. 45(2). 320–326. 38 indexed citations

10.

Buckley, Julliette M., Suzanne B. Coopey, John Sharko, et al.. (2012). The feasibility of using natural language processing to extract clinical information from breast pathology reports. Journal of Pathology Informatics. 3(1). 23–23. 88 indexed citations

11.

Byrne, Thomas N., Steven J. Isakoff, Sandra Rincon, & Thomas M. Gudewicz. (2012). Case 27-2012. New England Journal of Medicine. 367(9). 851–861. 6 indexed citations

12.

Kim, Jiyeon, Thomas M. Gudewicz, Anand S. Dighe, & John R. Gilbertson. (2010). The pathology informatics curriculum wiki: Harnessing the power of user-generated content. Journal of Pathology Informatics. 1(1). 10–10. 37 indexed citations

13.

Thomas, Tami L., et al.. (2003). Health of U.S. Navy submarine crew during periods of isolation.. PubMed. 74(3). 260–5. 9 indexed citations

14.

Levine, Barry, et al.. (1993). A Multiple Drug Intoxication Involving Cyclobenzaprine and Ibuprofen. American Journal of Forensic Medicine & Pathology. 14(3). 246–248. 10 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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