Dennis H. Murphree

2.7k total citations · 1 hit paper
72 papers, 1.7k citations indexed

About

Dennis H. Murphree is a scholar working on Epidemiology, Emergency Medicine and Surgery. According to data from OpenAlex, Dennis H. Murphree has authored 72 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Epidemiology, 18 papers in Emergency Medicine and 17 papers in Surgery. Recurrent topics in Dennis H. Murphree's work include Cardiac Arrest and Resuscitation (15 papers), Sepsis Diagnosis and Treatment (15 papers) and Machine Learning in Healthcare (9 papers). Dennis H. Murphree is often cited by papers focused on Cardiac Arrest and Resuscitation (15 papers), Sepsis Diagnosis and Treatment (15 papers) and Machine Learning in Healthcare (9 papers). Dennis H. Murphree collaborates with scholars based in United States, Canada and Ireland. Dennis H. Murphree's co-authors include Gregory W. Barsness, Jacob C. Jentzer, Brandon M. Wiley, Courtney Bennett, Mark T. Keegan, Arthur C. Guyton, K. W. Scheel, R. Scott Wright, Saraschandra Vallabhajosyula and Ognjen Gajic and has published in prestigious journals such as SHILAP Revista de lepidopterología, Blood and Journal of the American College of Cardiology.

In The Last Decade

Dennis H. Murphree

71 papers receiving 1.7k 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.

Electrocardiogram screening for aortic valve stenosis using artificial intelligence

2021 126 citations Michal Cohen‐Shelly, Zachi I. Attia et al. European Heart Journal profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dennis H. Murphree United States	24	603	494	420	395	375	72	1.7k
David N. Hager United States	23	374 0.6×	573 1.2×	285 0.7×	599 1.5×	460 1.2×	70	2.3k
Zhe Luo China	24	350 0.6×	220 0.4×	156 0.4×	438 1.1×	387 1.0×	164	2.5k
Joonghee Kim South Korea	25	306 0.5×	610 1.2×	81 0.2×	606 1.5×	263 0.7×	103	1.9k
Tezcan Ozrazgat‐Baslanti United States	28	760 1.3×	263 0.5×	120 0.3×	686 1.7×	655 1.7×	103	2.8k
Candice Downey United Kingdom	19	294 0.5×	187 0.4×	282 0.7×	216 0.5×	564 1.5×	33	1.2k
Yung‐Chang Chen Taiwan	30	358 0.6×	334 0.7×	279 0.7×	449 1.1×	443 1.2×	128	2.4k
Bart F. Geerts Netherlands	24	951 1.6×	159 0.3×	319 0.8×	337 0.9×	1.3k 3.5×	85	2.0k
Morteza Naghavi United States	22	738 1.2×	209 0.4×	264 0.6×	380 1.0×	505 1.3×	63	1.9k
James M. Blum United States	22	315 0.5×	227 0.5×	167 0.4×	266 0.7×	417 1.1×	79	1.8k
Denise P. Veelo Netherlands	24	687 1.1×	232 0.5×	198 0.5×	181 0.5×	1.0k 2.7×	103	2.0k

Countries citing papers authored by Dennis H. Murphree

Since Specialization

Citations

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

Fields of papers citing papers by Dennis H. Murphree

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dennis H. Murphree. 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 Dennis H. Murphree. The network helps show where Dennis H. Murphree may publish in the future.

Co-authorship network of co-authors of Dennis H. Murphree

This figure shows the co-authorship network connecting the top 25 collaborators of Dennis H. Murphree. A scholar is included among the top collaborators of Dennis H. Murphree 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 Dennis H. Murphree. Dennis H. Murphree 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

Jentzer, Jacob C., Ognjen Gajic, Vitaly Herasevich, et al.. (2025). Early prediction of shock in intensive care unit patients by machine learning using discrete electronic health record data. Journal of Critical Care. 88. 155093–155093. 1 indexed citations

Khan, Jibran, Nneka I. Comfere, Dennis H. Murphree, et al.. (2024). Foundation Models for Histopathology—Fanfare or Flair. SHILAP Revista de lepidopterología. 2(1). 165–174. 8 indexed citations

Harmon, David, Christopher G. Scott, Dennis H. Murphree, et al.. (2023). Postdevelopment Performance and Validation of the Artificial Intelligence-Enhanced Electrocardiogram for Detection of Cardiac Amyloidosis. JACC Advances. 2(8). 100612–100612. 18 indexed citations

Murphree, Dennis H., et al.. (2023). Artificial intelligence for automatic detection of basal cell carcinoma from frozen tissue tangential biopsies. Clinical and Experimental Dermatology. 49(7). 719–721. 7 indexed citations

Takahashi, Paul Y., Rozalina G. McCoy, Gregory J. Hanson, et al.. (2022). Risk Prediction Model for 6-Month Mortality for Patients Discharged to Skilled Nursing Facilities. Journal of the American Medical Directors Association. 23(8). 1403–1408. 7 indexed citations

Murphree, Dennis H., Patrick M. Wilson, Shusaku Asai, et al.. (2021). Improving the delivery of palliative care through predictive modeling and healthcare informatics. Journal of the American Medical Informatics Association. 28(6). 1065–1073. 31 indexed citations

Vallabhajosyula, Saraschandra, et al.. (2021). Temporal Trends, Management and Outcomes of Acute Myocardial Infarction with Concomitant Respiratory Infections. The American Journal of Cardiology. 150. 1–7. 4 indexed citations

Cohen‐Shelly, Michal, Zachi I. Attia, Paul A. Friedman, et al.. (2021). Electrocardiogram screening for aortic valve stenosis using artificial intelligence. European Heart Journal. 42(30). 2885–2896. 126 indexed citations breakdown →

Grogan, Martha, Francisco López-Jiménez, Michal Cohen‐Shelly, et al.. (2021). Artificial Intelligence–Enhanced Electrocardiogram for the Early Detection of Cardiac Amyloidosis. Mayo Clinic Proceedings. 96(11). 2768–2778. 76 indexed citations

10.

Quattrocchi, Enrica, et al.. (2020). β3 integrin immunohistochemistry as a method to predict sentinel lymph node status in patients with primary cutaneous melanoma. International Journal of Dermatology. 59(10). 1241–1248. 4 indexed citations

11.

Murphree, Dennis H., Lisa A. Drage, Michael Wang, et al.. (2020). Deep learning for dermatologists: Part I. Fundamental concepts. Journal of the American Academy of Dermatology. 87(6). 1343–1351. 35 indexed citations

12.

Vallabhajosyula, Saraschandra, Anna Subramaniam, Dennis H. Murphree, et al.. (2020). Complications from percutaneous-left ventricular assist devices versus intra-aortic balloon pump in acute myocardial infarction-cardiogenic shock. PLoS ONE. 15(8). e0238046–e0238046. 14 indexed citations

13.

Jentzer, Jacob C., Courtney Bennett, Brandon M. Wiley, et al.. (2019). Predictive value of individual Sequential Organ Failure Assessment sub-scores for mortality in the cardiac intensive care unit. PLoS ONE. 14(5). e0216177–e0216177. 31 indexed citations

14.

Jentzer, Jacob C., Nandan S. Anavekar, Brandon M. Wiley, et al.. (2019). Admission Braden Skin Score Independently Predicts Mortality in Cardiac Intensive Care Patients. Mayo Clinic Proceedings. 94(10). 1994–2003. 34 indexed citations

15.

Fitzgerald, Seán, Daying Dai, Dennis H. Murphree, et al.. (2019). Orbit image analysis machine learning software can be used for the histological quantification of acute ischemic stroke blood clots. PLoS ONE. 14(12). e0225841–e0225841. 52 indexed citations

16.

McCoy, Rozalina G., Björg Thorsteinsdottir, Rajeev Chaudhry, et al.. (2019). Risk of 30-Day Hospital Readmission Among Patients Discharged to Skilled Nursing Facilities: Development and Validation of a Risk-Prediction Model. Journal of the American Medical Directors Association. 20(4). 444–450.e2. 15 indexed citations

17.

Murphree, Dennis H., et al.. (2019). The Value of Aggregated High-Resolution Intraoperative Data for Predicting Post-Surgical Infectious Complications at Two Independent Sites. Studies in health technology and informatics. 264. 398–402. 3 indexed citations

18.

Jentzer, Jacob C., Dennis H. Murphree, Brandon M. Wiley, et al.. (2018). Comparison of Mortality Risk Prediction Among Patients ≥70 Versus <70 Years of Age in a Cardiac Intensive Care Unit. The American Journal of Cardiology. 122(10). 1773–1778. 62 indexed citations

19.

Bennett, Courtney, R. Scott Wright, Jacob C. Jentzer, et al.. (2018). Severity of illness assessment with application of the APACHE IV predicted mortality and outcome trends analysis in an academic cardiac intensive care unit. Journal of Critical Care. 50. 242–246. 86 indexed citations

20.

Ngufor, Che, Matthew A. Warner, Dennis H. Murphree, et al.. (2017). Identification of Clinically Meaningful Plasma Transfusion Subgroups Using Unsupervised Random Forest Clustering.. PubMed Central. 2017. 1332–1341. 7 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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