Morgan Simons

547 total citations · 1 hit paper
6 papers, 353 citations indexed

About

Morgan Simons is a scholar working on Epidemiology, Artificial Intelligence and Family Practice. According to data from OpenAlex, Morgan Simons has authored 6 papers receiving a total of 353 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Epidemiology, 3 papers in Artificial Intelligence and 2 papers in Family Practice. Recurrent topics in Morgan Simons's work include Machine Learning in Healthcare (3 papers), Sepsis Diagnosis and Treatment (3 papers) and Clinical Reasoning and Diagnostic Skills (2 papers). Morgan Simons is often cited by papers focused on Machine Learning in Healthcare (3 papers), Sepsis Diagnosis and Treatment (3 papers) and Clinical Reasoning and Diagnostic Skills (2 papers). Morgan Simons collaborates with scholars based in United States and Thailand. Morgan Simons's co-authors include Joseph Futoma, Finale Doshi‐Velez, Trishan Panch, Leo Anthony Celi, Marshall Nichols, Kristin Corey, Mark Sendak, Suresh Balu, Michael Gao and Armando Bedoya and has published in prestigious journals such as Journal of Pharmaceutical Sciences, Journal of the American College of Surgeons and The Lancet Digital Health.

In The Last Decade

Morgan Simons

6 papers receiving 348 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The myth of generalisability in clinical research and machine learning in health care

2020 252 citations Joseph Futoma, Morgan Simons et al. The Lancet Digital Health profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Morgan Simons United States	6	155	98	96	93	34	6	353
Meghan R. Hutch United States	5	133 0.9×	66 0.7×	77 0.8×	66 0.7×	22 0.6×	11	374
Stephanie L. Hyland United States	5	162 1.0×	71 0.7×	68 0.7×	87 0.9×	23 0.7×	10	338
Nathan Brajer United States	5	157 1.0×	160 1.6×	72 0.8×	111 1.2×	26 0.8×	5	384
Irfan Ahmed United Kingdom	6	86 0.6×	112 1.1×	76 0.8×	34 0.4×	22 0.6×	16	366
Anthony Lin United States	7	99 0.6×	82 0.8×	43 0.4×	93 1.0×	20 0.6×	16	433
Arash Kia United States	8	122 0.8×	68 0.7×	123 1.3×	66 0.7×	11 0.3×	23	345
Albert Buchard United Kingdom	6	77 0.5×	52 0.5×	78 0.8×	85 0.9×	14 0.4×	8	457
Rahul Thapa United States	10	162 1.0×	111 1.1×	52 0.5×	45 0.5×	14 0.4×	15	354
Andrew A. S. Soltan United Kingdom	10	150 1.0×	111 1.1×	104 1.1×	31 0.3×	18 0.5×	17	411
William Mitchell United States	9	59 0.4×	137 1.4×	110 1.1×	46 0.5×	34 1.0×	22	421

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-authorship network of co-authors of Morgan Simons

This figure shows the co-authorship network connecting the top 25 collaborators of Morgan Simons. A scholar is included among the top collaborators of Morgan Simons 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 Morgan Simons. Morgan Simons is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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6 of 6 papers shown

1.

Futoma, Joseph, Morgan Simons, Finale Doshi‐Velez, & Rishikesan Kamaleswaran. (2021). Generalization in Clinical Prediction Models: The Blessing and Curse of Measurement Indicator Variables. Critical Care Explorations. 3(7). e0453–e0453. 9 indexed citations

2.

Futoma, Joseph, Morgan Simons, Trishan Panch, Finale Doshi‐Velez, & Leo Anthony Celi. (2020). The myth of generalisability in clinical research and machine learning in health care. The Lancet Digital Health. 2(9). e489–e492. 252 indexed citations breakdown →

3.

Corey, Kristin, Joshua Helmkamp, Morgan Simons, et al.. (2020). Assessing Quality of Surgical Real-World Data from an Automated Electronic Health Record Pipeline. Journal of the American College of Surgeons. 230(3). 295–305e12. 6 indexed citations

4.

Bedoya, Armando, Joseph Futoma, Meredith E. Clement, et al.. (2020). Machine learning for early detection of sepsis: an internal and temporal validation study. JAMIA Open. 3(2). 252–260. 68 indexed citations

5.

Simons, Morgan, et al.. (2018). Full depth measurement of tenofovir transport in rectal mucosa using confocal Raman spectroscopy and optical coherence tomography. Drug Delivery and Translational Research. 8(3). 843–852. 9 indexed citations

6.

Maher, Jason R., et al.. (2016). Label-Free Measurements of Tenofovir Diffusion Coefficients in a Microbicide Gel Using Raman Spectroscopy. Journal of Pharmaceutical Sciences. 106(2). 639–644. 9 indexed citations

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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