Thomas E. Tavolara

561 citations
38 papers · 370 · h-index 12

Impact in

Papers in

Thomas E. Tavolara

36 papers receiving 360 citations

Peers

Thomas E. Tavolara
Comparison fields: 5 of 64
  • Health Informatics 26
  • Radiology, Nuclear Medicine and Imaging 113
  • Anesthesiology and Pain Medicine 23
  • Biophysics 26
  • Artificial Intelligence 144
Replace Sungwon Lee with:
Sungwon Lee United States
Fayu Liu China
Cláudia Freitas Portugal
Norbert Wey Switzerland
Mircea-Sebastian Şerbănescu Romania
Xinyi Du-Harpur United Kingdom
Brian L. Hill United States
Masoumeh Gity Iran
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Thomas E. Tavolara relative to Sungwon Lee United States Sungwon Lee's profile →
Citations per field
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Citations per year

Countries citing papers authored by Thomas E. Tavolara

Since Specialization
Citations

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

Fields of papers citing papers by Thomas E. Tavolara

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Thomas E. Tavolara, 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 Thomas E. Tavolara Line = papers co-authored together Thomas E. Tavolara links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202150
2 201837
3 202232
4 202131
5 202128
6 202023
7 201921
8 202319
9 202219
10 202016
11 202014
12 202313
13 20247
14 20246
15 20245
16 20205
17 20185
18 20194
19 20184
20 20214

About Thomas E. Tavolara

Thomas E. Tavolara is a scholar working on Artificial Intelligence, Oncology, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Infectious Diseases, having authored 38 papers that have together received 370 indexed citations. Recurring topics across this work include AI in cancer detection (17 papers), Radiomics and Machine Learning in Medical Imaging (11 papers), Colorectal Cancer Screening and Detection (8 papers), Digital Imaging for Blood Diseases (5 papers), Tuberculosis Research and Epidemiology (5 papers), Cell Image Analysis Techniques (4 papers), Cancer Genomics and Diagnostics (3 papers) and interferon and immune responses (3 papers). The work is most often cited by research in Health Informatics (26 citations), Radiology, Nuclear Medicine and Imaging (113 citations), Anesthesiology and Pain Medicine (23 citations), Biophysics (26 citations) and Artificial Intelligence (144 citations). Thomas E. Tavolara has collaborated with scholars based in United States, Hong Kong and Singapore. Frequent co-authors include Metin N. Gürcan, Muhammad Khalid Khan Niazi, Gillian Beamer, Scott Segal, Adam C. Gower, Liron Pantanowitz, Sang Jin Lee, Douglas J. Hartman, Daniel M. Gatti and Wendy L. Frankel. Their work appears in journals such as Diagnostic Pathology, PLoS ONE, PLoS Pathogens, EBioMedicine and Clinical Chemistry.

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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