Daniel Siegal

791 citations
25 papers · 575 · h-index 15

Impact in

Papers in

    • Shoulder Injury and Treatment 7
    • Orthopedic Surgery and Rehabilitation 3
    • Radiology practices and education 5
    • Ultrasound Imaging and Elastography 2
    • Radiomics and Machine Learning in Medical Imaging 2

Daniel Siegal

24 papers receiving 563 citations

Peers

Daniel Siegal
Comparison fields: 5 of 67
  • Orthopedics and Sports Medicine 137
  • Surgery 267
  • Medical Laboratory Technology 8
  • Internal Medicine 16
  • Health Informatics 7
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Siegal

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Siegal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Siegal. 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 Daniel Siegal. The network helps show where Daniel Siegal may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200984
2 201364
3 201752
4 200845
5 201742
6 200540
7 201639
8 201733
9 201426
10 200723
11 202018
12 202118
13 201717
14 201715
15 201015
16 20169
17 20058
18 20188
19
Automation of Protocoling Advanced MSK Examinations Using Natural Language Processing Techniques.
20237
20 20154

About Daniel Siegal

Daniel Siegal is a scholar working on Surgery, Radiology, Nuclear Medicine and Imaging, Epidemiology, Orthopedics and Sports Medicine and Infectious Diseases, having authored 25 papers that have together received 575 indexed citations. Recurring topics across this work include Shoulder Injury and Treatment (7 papers), Radiology practices and education (5 papers), Orthopedic Surgery and Rehabilitation (3 papers), Tendon Structure and Treatment (3 papers), Ultrasound Imaging and Elastography (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Venous Thromboembolism Diagnosis and Management (1 paper) and Cardiovascular Effects of Exercise (1 paper). The work is most often cited by research in Orthopedics and Sports Medicine (137 citations), Surgery (267 citations), Medical Laboratory Technology (8 citations), Internal Medicine (16 citations) and Health Informatics (7 citations). Daniel Siegal has collaborated with scholars based in United States, Spain and Israel. Frequent co-authors include Michael J. Bey, Marnix van Holsbeeck, Timothy G. Baumer, Mary G. Hochman, Jim S. Wu, Vasilios Moutzouros, Joel S. Newman, Burke A. Cunha, George Divine and Cathryn D. Peltz. Their work appears in journals such as Journal of the American College of Radiology, Skeletal Radiology, Heart & Lung, Clinical Orthopaedics and Related Research and Journal of Biomechanics.

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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