Jamie S. Hirsch

16.8k total citations · 1 hit paper
61 papers, 1.3k citations indexed

About

Jamie S. Hirsch is a scholar working on Infectious Diseases, Oncology and Epidemiology. According to data from OpenAlex, Jamie S. Hirsch has authored 61 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Infectious Diseases, 13 papers in Oncology and 12 papers in Epidemiology. Recurrent topics in Jamie S. Hirsch's work include COVID-19 Clinical Research Studies (20 papers), COVID-19 and healthcare impacts (12 papers) and Sepsis Diagnosis and Treatment (6 papers). Jamie S. Hirsch is often cited by papers focused on COVID-19 Clinical Research Studies (20 papers), COVID-19 and healthcare impacts (12 papers) and Sepsis Diagnosis and Treatment (6 papers). Jamie S. Hirsch collaborates with scholars based in United States, Netherlands and Canada. Jamie S. Hirsch's co-authors include Noémie Elhadad, Thomas McGinn, Kevin Coppa, Stuart L. Cohen, David M. Blei, Rajesh Ranganath, Adler Perotte, Karina W. Davidson, Theodoros P. Zanos and Douglas P. Barnaby and has published in prestigious journals such as Circulation, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Jamie S. Hirsch

54 papers receiving 1.2k 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.

Prevalence and Overlap of Cardiac, Renal, and Metabolic Conditions in US Adults, 1999-2020

2023 107 citations John W. Ostrominski, Jamie S. Hirsch et al. profile →

Peers

Jamie S. Hirsch

NEURO

ONCOL

EPIDE

SURGE

Christopher J. Tignanelli United States

Alex Milinovich United States

Vincent X. Liu United States

Jianyi Dai China

Ashish Verma United States

Kaiyue Diao China

Yuan Xu Canada

Ling Sang China

Michael Simonov United States

Andrew McGovern United Kingdom

Christopher J. Tignanelli United States

Jamie S. Hirsch

621 ×1.2

319 ×1.4

NEURO

254 ×1.2

ONCOL

309 ×1.7

EPIDE

435 ×3.0

SURGE

Citations per year, relative to Jamie S. Hirsch Jamie S. Hirsch (= 1×) peers Christopher J. Tignanelli

Countries citing papers authored by Jamie S. Hirsch

Since Specialization

Citations

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

Fields of papers citing papers by Jamie S. Hirsch

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jamie S. Hirsch. 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 Jamie S. Hirsch. The network helps show where Jamie S. Hirsch may publish in the future.

Co-authorship network of co-authors of Jamie S. Hirsch

This figure shows the co-authorship network connecting the top 25 collaborators of Jamie S. Hirsch. A scholar is included among the top collaborators of Jamie S. Hirsch 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 Jamie S. Hirsch. Jamie S. Hirsch 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

Hirsch, Jamie S., et al.. (2024). Optimizing Care Delivery in Patients with Chronic Kidney Disease in the United States: Proceedings of a Multidisciplinary Roundtable Discussion and Literature Review. Journal of Clinical Medicine. 13(5). 1206–1206. 1 indexed citations

Ostrominski, John W., et al.. (2024). Abstract P393: Trends in Risk Factor Control Among US Adults With Cardio-Kidney-Metabolic Multimorbidity, 1999-2020. Circulation. 149(Suppl_1).

Gupta, Shruti, Ilya Glezerman, Jamie S. Hirsch, et al.. (2024). Effect of Intravenous Magnesium on Cisplatin-Associated AKI. Journal of the American Society of Nephrology. 35(10S).

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

Levy, Todd, Kevin Coppa, Jamie S. Hirsch, et al.. (2023). Longitudinal dynamic clinical phenotypes of in-hospital COVID-19 patients across three dominant virus variants in New York. International Journal of Medical Informatics. 181. 105286–105286.

Levy, Todd, Kevin Coppa, Douglas P. Barnaby, et al.. (2022). Development and validation of self-monitoring auto-updating prognostic models of survival for hospitalized COVID-19 patients. Nature Communications. 13(1). 6812–6812. 11 indexed citations

Nair, Vinay, Jamie S. Hirsch, Nicholas Jandovitz, et al.. (2021). The Effect of Race Coefficients on Preemptive Listing for Kidney Transplantation. Journal of the American Society of Nephrology. 32(10S). 643–643. 3 indexed citations

Spyropoulos, Alex C., Stuart L. Cohen, Eugenia Gianos, et al.. (2021). Validation of the IMPROVE‐DD risk assessment model for venous thromboembolism among hospitalized patients with COVID‐19. Research and Practice in Thrombosis and Haemostasis. 5(2). 296–300. 27 indexed citations

10.

Bolourani, Siavash, Max Brenner, Ping Wang, et al.. (2021). A Machine Learning Prediction Model of Respiratory Failure Within 48 Hours of Patient Admission for COVID-19: Model Development and Validation. Journal of Medical Internet Research. 23(2). e24246–e24246. 69 indexed citations

11.

Giannis, Dimitrios, Matthew A. Barish, Mark Goldin, et al.. (2021). Incidence of Venous Thromboembolism and Mortality in Patients with Initial Presentation of COVID-19. Journal of Thrombosis and Thrombolysis. 51(4). 897–901. 30 indexed citations

12.

Goldin, Mark, Nina Kohn, Michael Qiu, et al.. (2021). External validation of the IMPROVE-DD risk assessment model for venous thromboembolism among inpatients with COVID-19. Journal of Thrombosis and Thrombolysis. 52(4). 1032–1035. 25 indexed citations

13.

Kim, Eun Ji, Kevin Coppa, Jamie S. Hirsch, et al.. (2021). Examination of patient characteristics and hydroxychloroquine use based on the US Food and Drug Administration’s recommendation: a cross-sectional analysis in New York. BMJ Open. 11(2). e042965–e042965. 3 indexed citations

14.

Gianos, Eugenia, Jane Cerise, Jamie S. Hirsch, et al.. (2021). Sex-Based Differences in COVID-19 Outcomes. Journal of Women s Health. 30(4). 492–501. 14 indexed citations

15.

Nair, Vinay, Nicholas Jandovitz, Jamie S. Hirsch, et al.. (2020). COVID-19 in kidney transplant recipients. American Journal of Transplantation. 20(7). 1819–1825. 172 indexed citations

16.

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

17.

Sachdeva, Mala, Nupur N. Uppal, Jamie S. Hirsch, et al.. (2020). COVID-19 in Hospitalized Patients on Chronic Peritoneal Dialysis: A Case Series. American Journal of Nephrology. 51(8). 669–674. 24 indexed citations

18.

Schwenk, Michael H., Jamie S. Hirsch, & Andrew S. Bomback. (2015). Aldosterone Blockade in CKD: Emphasis on Pharmacology. Advances in Chronic Kidney Disease. 22(2). 123–132. 29 indexed citations

19.

Tsapepas, Demetra, Spencer T. Martin, Alex Yang, et al.. (2014). Risk evaluation and mitigation strategy programs in solid organ transplantation: the promises of information technology. Journal of the American Medical Informatics Association. 21(e2). e358–e362. 3 indexed citations

20.

Hirsch, Jamie S., et al.. (2013). De novo Membranous Nephropathy in Renal Allograft Associated With Antibody-Mediated Rejection and Review of the Literature. Transplantation Proceedings. 45(9). 3424–3428. 10 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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