Morgan Simons

6 papers receiving 348 citations

Hit Papers

The myth of generalisability in clinical research and machine learning in health care 2020 · 252 citations
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Peers

Morgan Simons
Comparison fields: 5 of 90
  • Health Informatics 98
  • Family Practice 19
  • Health Information Management 31
  • Artificial Intelligence 155
  • Radiology, Nuclear Medicine and Imaging 96
Replace Albert Buchard with:
Albert Buchard France
Anthony Lin United States
Mathias Vassard Olsen Denmark
Fried-Michael Dahlweid Switzerland
Mohammed Saeed United Kingdom
Nathan Brajer United States
Stephanie L. Hyland United States
Hermione Poh Singapore
Thomas Gumbsch Switzerland
Morgan Simons relative to Albert Buchard France Albert Buchard's profile →
Citations per field
00.5×1.5×2.0×
Albert Buchard · 1×
Citations per year

Countries citing papers authored by Morgan Simons

Since Specialization
Citations

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

Fields of papers citing papers by Morgan Simons

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

6 of 6 papers shown
#Work
1
The myth of generalisability in clinical research and machine learning in health care
Hit paper breakdown →
2020252
2 202068
3 20189
4 20169
5 20219
6 20206

About Morgan Simons

Morgan Simons is a scholar working on Family Practice, Geriatrics and Gerontology, Health Information Management, Biophysics and Pharmaceutical Science, having authored 6 papers that have together received 353 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (3 papers), Sepsis Diagnosis and Treatment (3 papers), Clinical Reasoning and Diagnostic Skills (2 papers), Electronic Health Records Systems (1 paper), Hepatitis B Virus Studies (1 paper), Pharmaceutical Practices and Patient Outcomes (1 paper), Cardiac, Anesthesia and Surgical Outcomes (1 paper) and Advanced Drug Delivery Systems (1 paper). The work is most often cited by research in Health Informatics (98 citations), Family Practice (19 citations), Health Information Management (31 citations), Artificial Intelligence (155 citations) and Radiology, Nuclear Medicine and Imaging (96 citations). Morgan Simons has collaborated with scholars based in United States and Thailand. Frequent co-authors include Joseph Futoma, Finale Doshi‐Velez, Leo Anthony Celi, Trishan Panch, Marshall Nichols, Mark Sendak, Kristin Corey, Suresh Balu, Michael Gao and Katherine Heller. Their work appears in journals such as Journal of Pharmaceutical Sciences, Journal of the American College of Surgeons, The Lancet Digital Health, Drug Delivery and Translational Research and JAMIA Open.

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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