J.C. Rojas

818 total citations
31 papers, 394 citations indexed

About

J.C. Rojas is a scholar working on Emergency Medicine, Pulmonary and Respiratory Medicine and Epidemiology. According to data from OpenAlex, J.C. Rojas has authored 31 papers receiving a total of 394 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Emergency Medicine, 6 papers in Pulmonary and Respiratory Medicine and 6 papers in Epidemiology. Recurrent topics in J.C. Rojas's work include Emergency and Acute Care Studies (8 papers), Hospital Admissions and Outcomes (5 papers) and Heart Failure Treatment and Management (4 papers). J.C. Rojas is often cited by papers focused on Emergency and Acute Care Studies (8 papers), Hospital Admissions and Outcomes (5 papers) and Heart Failure Treatment and Management (4 papers). J.C. Rojas collaborates with scholars based in United States, Chile and Costa Rica. J.C. Rojas's co-authors include Patrick G. Lyons, Lekshmi Santhosh, Kyle A. Carey, Matthew M. Churpek, Laura Ruth Venable, Dana P. Edelson, Michael D. Howell, Mark Siegler, Esha M. Kapania and Gina M. Piscitello and has published in prestigious journals such as SHILAP Revista de lepidopterología, Gastroenterology and American Journal of Respiratory and Critical Care Medicine.

In The Last Decade

J.C. Rojas

26 papers receiving 386 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
J.C. Rojas United States 9 98 83 82 67 59 31 394
Heather Gardner United States 8 188 1.9× 104 1.3× 81 1.0× 40 0.6× 33 0.6× 14 410
Kumiko O. Schnock United States 14 98 1.0× 93 1.1× 82 1.0× 174 2.6× 60 1.0× 38 557
Mor Saban Israel 13 56 0.6× 121 1.5× 48 0.6× 25 0.4× 36 0.6× 91 680
Justin D. Schrager United States 14 263 2.7× 86 1.0× 80 1.0× 31 0.5× 120 2.0× 21 622
Jonathan Bae United States 11 54 0.6× 45 0.5× 39 0.5× 89 1.3× 75 1.3× 22 492
Courtney C. Kuza United States 12 99 1.0× 145 1.7× 54 0.7× 42 0.6× 274 4.6× 23 520
Amanda J Moy United States 10 41 0.4× 48 0.6× 61 0.7× 54 0.8× 79 1.3× 19 432
Srinivasan Suresh United States 12 92 0.9× 65 0.8× 13 0.2× 26 0.4× 102 1.7× 44 408
Jessica Schwartz United States 13 57 0.6× 86 1.0× 118 1.4× 39 0.6× 146 2.5× 27 558
Sridevi Sridharan United States 13 25 0.3× 85 1.0× 74 0.9× 26 0.4× 65 1.1× 38 440

Countries citing papers authored by J.C. Rojas

Since Specialization
Citations

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

Fields of papers citing papers by J.C. Rojas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J.C. Rojas. 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 J.C. Rojas. The network helps show where J.C. Rojas may publish in the future.

Co-authorship network of co-authors of J.C. Rojas

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

All Works

20 of 20 papers shown
1.
Chen, Elaine, et al.. (2025). Discussing End-of-Life in the Intensive Care Unit: Education Practices in Pulmonary and Critical Care Medicine Fellowship Programs. American Journal of Hospice and Palliative Medicine®. 43(5). 512–519.
2.
Chaudhari, Vikram, et al.. (2025). Streamlining Intensive Care Unit (ICU) Family Communication: Evaluation of Large Language Models for Generating Daily Written Patient Care Summaries. American Journal of Respiratory and Critical Care Medicine. 211(Supplement_1). A7390–A7390.
3.
Carey, Kyle A., et al.. (2025). Comparison of Chart Review and Administrative Data in Developing Predictive Models for Readmissions in Chronic Obstructive Pulmonary Disease. Chronic Obstructive Pulmonary Diseases Journal of the COPD Foundation. 12(2). 175–183. 1 indexed citations
4.
Lyons, Patrick G., et al.. (2024). Validating the Physician Documentation Quality Instrument for Intensive Care Unit–Ward Transfer Notes. ATS Scholar. 5(2). 274–285. 1 indexed citations
5.
6.
Fukui, Elle, et al.. (2023). Improving Communication in Intensive Care Unit to Ward Transitions: Protocol for Multisite National Implementation of the ICU-PAUSE Handoff Tool. JMIR Research Protocols. 12. e40918–e40918. 3 indexed citations
7.
Press, Valerie G., William F. Parker, J.C. Rojas, et al.. (2023). Association of preadmission insomnia symptoms with objective in-hospital sleep and clinical outcomes among hospitalized patients. Journal of Clinical Sleep Medicine. 20(5). 681–687.
8.
Friedman, Eleanor E., et al.. (2023). No-show Prediction Model Performance Among People With HIV: External Validation Study. Journal of Medical Internet Research. 25. e43277–e43277.
9.
Joyce, Cara, Talar Markossian, Hale M. Thompson, et al.. (2022). The Evaluation of a Clinical Decision Support Tool Using Natural Language Processing to Screen Hospitalized Adults for Unhealthy Substance Use: Protocol for a Quasi-Experimental Design. JMIR Research Protocols. 11(12). e42971–e42971. 2 indexed citations
10.
Santhosh, Lekshmi, et al.. (2022). Cocreating the ICU-PAUSE Tool for Intensive Care Unit–Ward Transitions. ATS Scholar. 3(2). 312–323. 8 indexed citations
11.
Rojas, J.C., et al.. (2022). Care Quality for Patients with Chronic Obstructive Pulmonary Disease in the Readmission Penalty Era. American Journal of Respiratory and Critical Care Medicine. 207(1). 29–37. 5 indexed citations
12.
Rojas, J.C., et al.. (2022). Using Machine Learning to Predict Likelihood and Cause of Readmission After Hospitalization for Chronic Obstructive Pulmonary Disease Exacerbation. International Journal of COPD. Volume 17. 2701–2709. 7 indexed citations
13.
Rojas, J.C., John Fahrenbach, Scott C. Cook, et al.. (2022). Framework for Integrating Equity Into Machine Learning Models. CHEST Journal. 161(6). 1621–1627. 32 indexed citations
14.
15.
Santhosh, Lekshmi, J.C. Rojas, & Patrick G. Lyons. (2021). Zooming into Focus Groups: Strategies for Qualitative Research in the Era of Social Distancing. ATS Scholar. 2(2). 176–184. 50 indexed citations
16.
Patel, Ajanta, et al.. (2021). Integrating Physicians Into Lean Quality Improvement Through a Structured Educational Program. American Journal of Medical Quality. 37(1). 6–13. 1 indexed citations
17.
Rojas, J.C., Patrick G. Lyons, Kyle A. Carey, et al.. (2020). Accuracy of Clinicians’ Ability to Predict the Need for Intensive Care Unit Readmission. Annals of the American Thoracic Society. 17(7). 847–853. 9 indexed citations
18.
Rojas, J.C.. (2019). EL CAPITAL INTELECTUAL Y EL CONOCIMIENTO: GENERANDO VENTAJAS COMPETITIVAS EN LAS EMPRESAS. 1(5). 160–168. 2 indexed citations
19.
Rojas, J.C., Kyle A. Carey, Dana P. Edelson, et al.. (2018). Predicting Intensive Care Unit Readmission with Machine Learning Using Electronic Health Record Data. Annals of the American Thoracic Society. 15(7). 846–853. 109 indexed citations
20.
Rojas, J.C., et al.. (1989). Criterios bacteriológicos y calidad sanitaria de las aguas de las playas de Costa Rica, período 1986-1987. Dialnet (Universidad de la Rioja). 9(3). 45–59. 1 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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