David Magnus

69 papers receiving 2.3k citations

Hit Papers

Implementing Machine Learning in Health Care — Addressing...20182026202020232018250500750

Peers

David Magnus
Comparison fields: 5 of 156
  • Public Health, Environmental and Occupational Health 804
  • Health Informatics 619
  • General Health Professions 436
  • Artificial Intelligence 340
  • Radiology, Nuclear Medicine and Imaging 312
Replace Ravi B. Parikh with:
Ravi B. Parikh United States
Mahiben Maruthappu United Kingdom
Gabriela Schmajuk United States
Shabbir Syed-Abdul Taiwan
Karen I. Kroeker Canada
Mark Sendak United States
Chris Sidey‐Gibbons United States
Izet Mašić Bosnia and Herzegovina
Kyu Rhee United States
Milena Gianfrancesco United States
David Magnus relative to Ravi B. Parikh United States Ravi B. Parikh's profile →
Citations per field
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Ravi B. Parikh · 1×
Citations per year

Countries citing papers authored by David Magnus

Since Specialization
Citations

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

Fields of papers citing papers by David Magnus

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Magnus

This figure shows the co-authorship network connecting the top 25 collaborators of David Magnus. A scholar is included among the top collaborators of David Magnus based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David Magnus. David Magnus is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
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Informational risk, institutional review, and autonomy in the proposed changes to the common rule.
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About David Magnus

David Magnus is a scholar working on Health Informatics, Public Health, Environmental and Occupational Health and Radiological and Ultrasound Technology, having authored 70 papers that have together received 2.4k indexed citations. Recurring topics across this work include Ethics in Clinical Research (27 papers), Biomedical Ethics and Regulation (14 papers) and Ethics in medical practice (14 papers). The work is most often cited by research in Health Informatics (619 citations), Health Information Management (224 citations) and Public Health, Environmental and Occupational Health (804 citations). David Magnus has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Nigam H. Shah, Danton Char, Mildred K. Cho, Benjamin S. Wilfond, Sarah Rodgers, Arthur L. Caplan, Anthony Avery, Nicole Martinez‐Martin, Sandra Soo‐Jin Lee and Curtis P. Langlotz. Their work appears in journals such as Science, New England Journal of Medicine and Proceedings of the National Academy of Sciences.

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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