Marc D. Succi

59 papers receiving 1.4k citations

Marc D. Succi's Hit Papers

Assessing the Utility of ChatGPT Throughout the Entire Clinical Workflow: Development and Usability Study 2023 · 228 citations
2280+3+7Years since publication100200300

Peers

Marc D. Succi
Comparison fields: 5 of 140
  • Health Informatics 460
  • Family Practice 53
  • Radiology, Nuclear Medicine and Imaging 414
  • Pharmaceutical Science 92
  • Molecular Medicine 75
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Countries citing papers authored by Marc D. Succi

Since Specialization
Citations

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

Fields of papers citing papers by Marc D. Succi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marc D. Succi. 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 Marc D. Succi. The network helps show where Marc D. Succi may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 65 papers — load more, or switch the sort, to bring in the rest.

#Work
1
An inflammation-targeting hydrogel for local drug delivery in inflammatory bowel disease
Hit paper breakdown →
2015360
2
Assessing the Utility of ChatGPT Throughout the Entire Clinical Workflow: Development and Usability Study
Hit paper breakdown →
2023228
3 2023189
4 201374
5 202162
6 202240
7 202034
8 202232
9 202129
10 202024
11 202119
12 202318
13 202418
14 201815
15 202015
16 202215
17 202114
18 202314
19 202113
20 202112

About Marc D. Succi

Marc D. Succi is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, Health Informatics, Oncology and General Health Professions, having authored 65 papers that have together received 1.4k indexed citations. Recurring topics across this work include Radiology practices and education (13 papers), Artificial Intelligence in Healthcare and Education (13 papers), COVID-19 and healthcare impacts (11 papers), COVID-19 diagnosis using AI (9 papers), Ultrasound in Clinical Applications (9 papers), Biomedical and Engineering Education (8 papers), Health and Medical Research Impacts (7 papers) and Radiation Dose and Imaging (7 papers). The work is most often cited by research in Health Informatics (460 citations), Family Practice (53 citations), Radiology, Nuclear Medicine and Imaging (414 citations), Pharmaceutical Science (92 citations) and Molecular Medicine (75 citations). Marc D. Succi has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Arya Rao, Keith J. Dreyer, John Kim, Winston Lie, Michael Pang, Meghana Kamineni, Róbert Langer, Adam Landman, Matthew J. Hamilton and Bonnie Cao. Their work appears in journals such as Journal of the American College of Radiology, The American Journal of Emergency Medicine, Academic Radiology, Nature Biotechnology and Scientific Reports.

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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