David Yankelevitz

3.7k citations
15 papers · 683 · h-index 10

Impact in

Papers in

David Yankelevitz

14 papers receiving 654 citations

Peers

David Yankelevitz
Comparison fields: 5 of 72
  • Radiology, Nuclear Medicine and Imaging 284
  • Pulmonary and Respiratory Medicine 381
  • Health Informatics 7
  • Cancer Research 47
  • Artificial Intelligence 121
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Shaimaa Bakr United States
Yoshiko Yamashita Japan
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Elżbieta Łuczyńska Poland
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Citations per field
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Citations per year

Countries citing papers authored by David Yankelevitz

Since Specialization
Citations

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

Fields of papers citing papers by David Yankelevitz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 2004313
2 2019113
3 201086
4 200742
5 200931
6 200829
7 200819
8 200816
9 200814
10 20079
11 20245
12
Increased uptake of 18F-fluorodeoxyglucose due to Mycobacterium avium complex in a solitary pulmonary nodule.
20084
13
Abstract 12003: Effects of Iterative Reconstruction on Coronary Artery Calcium Scoring
20121
14 20101
15 20250

About David Yankelevitz

David Yankelevitz is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, Oncology, Physiology and Biomedical Engineering, having authored 15 papers that have together received 683 indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (8 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Lung Cancer Treatments and Mutations (3 papers), Medical Imaging Techniques and Applications (2 papers), Gastric Cancer Management and Outcomes (2 papers), Angiogenesis and VEGF in Cancer (1 paper), Lung Cancer Research Studies (1 paper) and Hepatocellular Carcinoma Treatment and Prognosis (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (284 citations), Pulmonary and Respiratory Medicine (381 citations), Health Informatics (7 citations), Cancer Research (47 citations) and Artificial Intelligence (121 citations). David Yankelevitz has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Anthony P. Reeves, Ella A. Kazerooni, Samuel G. Armato, Laurence P. Clarke, Barbara Y. Croft, Charles R. Meyer, Michael F. McNitt‐Gray, Heber MacMahon, Geoffrey McLennan and Eric A. Hoffman. Their work appears in journals such as Journal of Clinical Oncology, Circulation, Radiology, Biomarkers and Journal of Thoracic Oncology.

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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