Mitchell D. Feldman

79 papers receiving 4.2k citations

Mitchell D. Feldman's Hit Papers

Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning Approach 2016 · 362 citations
3620+4+9Years since publication100200300

Peers

Mitchell D. Feldman
Comparison fields: 5 of 154
  • Medical Terminology 22
  • Health Informatics 108
  • Family Practice 114
  • Social Psychology 1.0k
  • Gender Studies 383
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Thomas K. Houston United States
Scott M. Wright United States
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Mark W. Friedberg United States
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Citations per year

Countries citing papers authored by Mitchell D. Feldman

Since Specialization
Citations

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

Fields of papers citing papers by Mitchell D. Feldman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mitchell D. Feldman. 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 Mitchell D. Feldman. The network helps show where Mitchell D. Feldman may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005460
2
Characteristics of Successful and Failed Mentoring Relationships
Hit paper breakdown →
2012398
3
Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning Approach
Hit paper breakdown →
2016362
4 2008328
5 2017261
6 2006219
7 2010215
8 2016193
9 2011184
10 2016129
11 2010107
12 201084
13 200972
14 201369
15 201266
16 201063
17 201261
18 201059
19 200757
20 201056

About Mitchell D. Feldman

Mitchell D. Feldman is a scholar working on Social Psychology, General Health Professions, Public Health, Environmental and Occupational Health, Clinical Psychology and Gender Studies, having authored 82 papers that have together received 4.5k indexed citations. Recurring topics across this work include Mentoring and Academic Development (13 papers), Mental Health Treatment and Access (12 papers), Health and Medical Research Impacts (9 papers), Diversity and Career in Medicine (9 papers), Innovations in Medical Education (7 papers), HIV/AIDS Research and Interventions (6 papers), Sepsis Diagnosis and Treatment (4 papers) and Child and Adolescent Psychosocial and Emotional Development (4 papers). The work is most often cited by research in Medical Terminology (22 citations), Health Informatics (108 citations), Family Practice (114 citations), Social Psychology (1.0k citations) and Gender Studies (383 citations). Mitchell D. Feldman has collaborated with scholars based in United States, Japan and Canada. Frequent co-authors include Richard L. Kravitz, Mallory O. Johnson, Ritankar Das, Peter Franks, Sharon E. Straus, Christine Marquez, Ronald M. Epstein, Leah Karliner, Jeffrey A. Tice and David Shimabukuro. Their work appears in journals such as Journal of General Internal Medicine, PLoS ONE, The American Journal of Medicine, Academic Medicine and Clinical and Translational Science.

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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