Michael Oppenheim

447 total citations
25 papers, 300 citations indexed

About

Michael Oppenheim is a scholar working on Surgery, Health Information Management and General Health Professions. According to data from OpenAlex, Michael Oppenheim has authored 25 papers receiving a total of 300 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Surgery, 6 papers in Health Information Management and 5 papers in General Health Professions. Recurrent topics in Michael Oppenheim's work include Healthcare Technology and Patient Monitoring (6 papers), Electronic Health Records Systems (5 papers) and Emergency and Acute Care Studies (3 papers). Michael Oppenheim is often cited by papers focused on Healthcare Technology and Patient Monitoring (6 papers), Electronic Health Records Systems (5 papers) and Emergency and Acute Care Studies (3 papers). Michael Oppenheim collaborates with scholars based in United States, Canada and India. Michael Oppenheim's co-authors include Vimla L. Patel, J Horský, David R. Kaufman, Jamie S. Hirsch, William Frayer, Ferdinand Velasco, Joseph Hayes, Cristina Vidal, Mary Reich Cooper and Joseph Conigliaro and has published in prestigious journals such as New England Journal of Medicine, Nature Communications and Journal of the American Academy of Dermatology.

In The Last Decade

Michael Oppenheim

25 papers receiving 294 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael Oppenheim United States	9	115	63	54	45	41	25	300
Eric Pifer United States	7	251 2.2×	95 1.5×	77 1.4×	47 1.0×	126 3.1×	8	384
NR Samaranayake Sri Lanka	11	56 0.5×	26 0.4×	77 1.4×	34 0.8×	97 2.4×	30	293
Rosy Tsopra France	13	92 0.8×	24 0.4×	15 0.3×	83 1.8×	37 0.9×	42	401
Jos Aarts Netherlands	8	224 1.9×	103 1.6×	74 1.4×	41 0.9×	123 3.0×	17	356
Katrina Richardson Australia	10	174 1.5×	59 0.9×	100 1.9×	41 0.9×	137 3.3×	16	314
Jonathan Austrian United States	14	94 0.8×	60 1.0×	37 0.7×	111 2.5×	26 0.6×	25	532
Kendall Rogers United States	8	124 1.1×	37 0.6×	43 0.8×	65 1.4×	29 0.7×	11	324
Sunila R. Kalkar Canada	8	170 1.5×	156 2.5×	93 1.7×	45 1.0×	107 2.6×	11	636
Adam Keene United States	10	34 0.3×	47 0.7×	93 1.7×	42 0.9×	10 0.2×	25	356
Juan D. Chaparro United States	10	97 0.8×	55 0.9×	38 0.7×	39 0.9×	20 0.5×	19	297

Countries citing papers authored by Michael Oppenheim

Since Specialization

Citations

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

Fields of papers citing papers by Michael Oppenheim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Oppenheim

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

All Works

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20 of 20 papers shown

Friedmann, B, et al.. (2025). Development and validation of a clinical wearable deep learning based continuous inhospital deterioration prediction model. Nature Communications. 16(1). 9513–9513. 1 indexed citations

Coppa, Kevin, et al.. (2023). Application of a Machine Learning Algorithm to Develop and Validate a Prediction Model for Ambulatory Non-Arrivals. Journal of General Internal Medicine. 38(10). 2298–2307. 3 indexed citations

Cohen, Jessica, et al.. (2022). Automated Identification of Patients with Advanced Illness.. PubMed. 2022. 269–278. 1 indexed citations

Khatri, Akshay, Prashant Malhotra, Angela Kim, et al.. (2021). Hospital-Acquired Bloodstream Infections in Patients Hospitalized With Severe Acute Respiratory Syndrome Coronavirus 2 Infection (Coronavirus Disease 2019): Association With Immunosuppressive Therapies. Open Forum Infectious Diseases. 8(7). ofab339–ofab339. 22 indexed citations

Coppa, Kevin, et al.. (2021). Examination of Post-discharge Follow-up Appointment Status and 30-Day Readmission. Journal of General Internal Medicine. 36(5). 1214–1221. 23 indexed citations

Hirsch, Jamie S., et al.. (2021). Design, development, and deployment of an indication- and kidney function-based decision support tool to optimize treatment and reduce medication dosing errors. JAMIA Open. 4(2). ooab039–ooab039. 5 indexed citations

Barnaby, Douglas P., Michael Oppenheim, Yousef Al‐Abed, et al.. (2020). Let Sleeping Patients Lie, avoiding unnecessary overnight vitals monitoring using a clinically based deep-learning model. npj Digital Medicine. 3(1). 149–149. 18 indexed citations

Hirsch, Jamie S., et al.. (2020). An approach to predicting patient experience through machine learning and social network analysis. Journal of the American Medical Informatics Association. 27(12). 1834–1843. 16 indexed citations

Richardson, Safiya, Stuart L. Cohen, Sundas Khan, et al.. (2019). Higher Imaging Yield When Clinical Decision Support Is Used. Journal of the American College of Radiology. 17(4). 496–503. 12 indexed citations

10.

Garg, Amit, et al.. (2017). Clinical Factors Associated with Readmission among Patients with Lower Limb Cellulitis. Dermatology. 233(1). 58–63. 6 indexed citations

11.

Garg, Amit, et al.. (2017). Clinical characteristics associated with days to discharge among patients admitted with a primary diagnosis of lower limb cellulitis. Journal of the American Academy of Dermatology. 76(4). 626–631. 14 indexed citations

12.

Oppenheim, Michael. (2016). Contemporary Psychoanalysis and Modern Jewish Philosophy. 1 indexed citations

13.

Oppenheim, Michael, et al.. (2011). Outstanding Business Reference Sources. Reference & User Services Quarterly. 51(2). 122–126. 1 indexed citations

14.

Bearman, Gonzalo, Michael Oppenheim, Eneida A. Mendonça, et al.. (2010). A Clinical Predictive Model for Catheter Related Bloodstream Infections from the Electronic Medical Record. 3(1). 1 indexed citations

15.

Oppenheim, Michael, et al.. (2009). ClinRefLink: implementation of infobutton-like functionality in a commercial clinical information system incorporating concepts from textual documents.. PubMed. 2009. 487–91. 2 indexed citations

16.

Horský, J, David R. Kaufman, Michael Oppenheim, & Vimla L. Patel. (2003). A framework for analyzing the cognitive complexity of computer-assisted clinical ordering. Journal of Biomedical Informatics. 36(1-2). 4–22. 100 indexed citations

17.

Oppenheim, Michael, et al.. (2000). Design of a clinical alert system to facilitate development, testing, maintenance, and user-specific notification.. PubMed. 630–4. 13 indexed citations

18.

Wilson, Yvonne, et al.. (1997). Local publications and resources. Journal of Government Information. 24(6). 519–524. 2 indexed citations

19.

Oppenheim, Michael, Michael Factor, & Dean F. Sittig. (1992). BIO-SPEAD: a parallel computing environment to accelerate development of biologic signal processing algorithms. Computer Methods and Programs in Biomedicine. 37(2). 137–147. 4 indexed citations

20.

Oppenheim, Michael. (1990). Three-Dimensional Neuroimaging. The Yale Journal of Biology and Medicine. 63(6). 602–603. 5 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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