Michael E. Zapadka

750 citations
20 papers · 489 indexed · 1 hit paper · h-index 10

Impact in

Papers in

Michael E. Zapadka

19 papers receiving 484 citations

Hit Papers

Translating radiology reports into plain language using ChatGPT and GPT-4 with prompt learning: results, limitations, and potential 2023 · 220 citations
220202320262024202550100150200

Peers

Michael E. Zapadka
Comparison fields: 5 of 97
  • Health Informatics 158
  • Radiology, Nuclear Medicine and Imaging 210
  • Family Practice 14
  • Genetics 37
  • Developmental Neuroscience 14
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Siddharth Nath Canada
Martin Májovský Czechia
Hiroyuki Tatekawa Japan
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Omri Bar United States
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Hirotaka Takita Japan
Emily B. Ambinder United States
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Citations per year

Countries citing papers authored by Michael E. Zapadka

Since Specialization
Citations

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

Fields of papers citing papers by Michael E. Zapadka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20241
2
Translating radiology reports into plain language using ChatGPT and GPT-4 with prompt learning: results, limitations, and potential
Hit paper breakdown →
2023220
3 20232
4 20211
5 20202
6 20200
7 201922
8 20181
9 20189
10 20172
11 201726
12 20135
13 20134
14 201313
15 201218
16 201215
17 201262
18 201134
19 201050
20 20102

About Michael E. Zapadka

Michael E. Zapadka is a scholar working on Health Informatics, Otorhinolaryngology, Neurology, Internal Medicine and Radiology, Nuclear Medicine and Imaging, having authored 20 papers that have together received 489 indexed citations. Recurring topics across this work include Ear Surgery and Otitis Media (3 papers), Vestibular and auditory disorders (3 papers), Head and Neck Anomalies (2 papers), Glioma Diagnosis and Treatment (2 papers), Radiation Dose and Imaging (2 papers), Congenital heart defects research (2 papers), Advanced MRI Techniques and Applications (2 papers) and Artificial Intelligence in Healthcare and Education (2 papers). The work is most often cited by research in Health Informatics (158 citations), Radiology, Nuclear Medicine and Imaging (210 citations), Family Practice (14 citations), Genetics (37 citations) and Developmental Neuroscience (14 citations). Michael E. Zapadka has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Christopher T. Whitlow, Qing Lyu, Chuang Niu, Janardhana Ponnatapura, Kyle J. Myers, Ge Wang, Josh Tan, Eric M. Lyders, Michael Y. M. Chen and Annette J. Johnson. Their work appears in journals such as American Journal of Neuroradiology, International Journal of Pediatric Otorhinolaryngology, Journal of Computer Assisted Tomography, Biological Psychiatry and Acta Anaesthesiologica Scandinavica.

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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