Eilon Gabel

896 total citations
22 papers, 512 citations indexed

About

Eilon Gabel is a scholar working on Surgery, Cardiology and Cardiovascular Medicine and Health Information Management. According to data from OpenAlex, Eilon Gabel has authored 22 papers receiving a total of 512 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Surgery, 9 papers in Cardiology and Cardiovascular Medicine and 5 papers in Health Information Management. Recurrent topics in Eilon Gabel's work include Cardiac, Anesthesia and Surgical Outcomes (9 papers), Hemodynamic Monitoring and Therapy (5 papers) and Electronic Health Records Systems (4 papers). Eilon Gabel is often cited by papers focused on Cardiac, Anesthesia and Surgical Outcomes (9 papers), Hemodynamic Monitoring and Therapy (5 papers) and Electronic Health Records Systems (4 papers). Eilon Gabel collaborates with scholars based in United States, United Kingdom and Israel. Eilon Gabel's co-authors include Ira Hofer, Maxime Cannesson, Pierre Baldi, Christine K. Lee, Christine Lee, Michael A. Pfeffer, Aman Mahajan, Bala G. Nair, Howard A. Schwid and Kumar Rajaram and has published in prestigious journals such as Annals of the New York Academy of Sciences, Genome biology and Anesthesiology.

In The Last Decade

Eilon Gabel

21 papers receiving 506 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eilon Gabel United States 12 264 260 90 65 63 22 512
Sarah Mullin United States 5 425 1.6× 238 0.9× 15 0.2× 25 0.4× 23 0.4× 15 648
Ivana Jankovic United States 9 255 1.0× 243 0.9× 30 0.3× 29 0.4× 35 0.6× 24 506
Rak Kyeong Choi South Korea 13 428 1.6× 182 0.7× 36 0.4× 53 0.8× 70 1.1× 45 592
Jing‐chao Luo China 12 110 0.4× 124 0.5× 14 0.2× 31 0.5× 121 1.9× 48 541
Elizabeth Lorenzi United States 6 62 0.2× 43 0.2× 38 0.4× 42 0.6× 33 0.5× 15 273
Hyue Mee Kim South Korea 18 615 2.3× 114 0.4× 39 0.4× 54 0.8× 120 1.9× 41 868
Sergio Sanchez‐Martinez Spain 8 276 1.0× 56 0.2× 101 1.1× 89 1.4× 73 1.2× 16 537
Joaquim Viana Portugal 13 68 0.3× 164 0.6× 5 0.1× 19 0.3× 92 1.5× 40 476
Joseph B. Leader United States 13 296 1.1× 112 0.4× 18 0.2× 52 0.8× 74 1.2× 23 748
Mustafa Khanbhai United Kingdom 11 40 0.2× 135 0.5× 14 0.2× 33 0.5× 26 0.4× 23 353

Countries citing papers authored by Eilon Gabel

Since Specialization
Citations

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

Fields of papers citing papers by Eilon Gabel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eilon Gabel

This figure shows the co-authorship network connecting the top 25 collaborators of Eilon Gabel. A scholar is included among the top collaborators of Eilon Gabel 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 Eilon Gabel. Eilon Gabel 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.
Epstein, Richard H., Eilon Gabel, Girish N. Nadkarni, et al.. (2025). Postoperative acute kidney injury is associated with persistent renal dysfunction: a multicentre propensity-matched cohort study. BJA Open. 14. 100384–100384.
2.
3.
Zarrin, David, Bilwaj Gaonkar, Bayard Wilson, et al.. (2024). Machine learning predicts cerebral vasospasm in patients with subarachnoid haemorrhage. EBioMedicine. 105. 105206–105206. 7 indexed citations
4.
Chang, Linda, et al.. (2024). Comparing Scoring Consistency of Large Language Models with Faculty for Formative Assessments in Medical Education. Journal of General Internal Medicine. 40(1). 127–134. 5 indexed citations
5.
6.
Wilson, Bayard, et al.. (2022). Early Postoperative Opioid Requirement Is Associated With Later Pain Control Needs After Supratentorial Craniotomies. Journal of Neurosurgical Anesthesiology. 35(3). 307–312. 3 indexed citations
7.
Mišić, Velibor V., Kumar Rajaram, & Eilon Gabel. (2021). A simulation-based evaluation of machine learning models for clinical decision support: application and analysis using hospital readmission. npj Digital Medicine. 4(1). 98–98. 23 indexed citations
8.
Hofer, Ira, Christine Lee, Eilon Gabel, Pierre Baldi, & Maxime Cannesson. (2020). Development and validation of a deep neural network model to predict postoperative mortality, acute kidney injury, and reintubation using a single feature set. npj Digital Medicine. 3(1). 58–58. 50 indexed citations
9.
Epstein, Richard H., Ira Hofer, Valiollah Salari, & Eilon Gabel. (2020). Successful Implementation of a Perioperative Data Warehouse Using Another Hospital’s Published Specification From Epic’s Electronic Health Record System. Anesthesia & Analgesia. 132(2). 465–474. 13 indexed citations
10.
Grogan, Tristan, et al.. (2020). Hydromorphone Unit Dose Affects Intraoperative Dosing. Anesthesiology. 132(5). 981–991. 8 indexed citations
11.
Hill, Brian L., Robert J. Brown, Eilon Gabel, et al.. (2019). An automated machine learning-based model predicts postoperative mortality using readily-extractable preoperative electronic health record data. British Journal of Anaesthesia. 123(6). 877–886. 55 indexed citations
12.
13.
Rahmani, Elior, Regev Schweiger, Liat Shenhav, et al.. (2018). BayesCCE: a Bayesian framework for estimating cell-type composition from DNA methylation without the need for methylation reference. Genome biology. 19(1). 141–141. 36 indexed citations
14.
Lee, Christine K., Ira Hofer, Eilon Gabel, Pierre Baldi, & Maxime Cannesson. (2018). Development and Validation of a Deep Neural Network Model for Prediction of Postoperative In-hospital Mortality. Anesthesiology. 129(4). 649–662. 127 indexed citations
15.
Hsu, Derek Y. & Eilon Gabel. (2018). Rigid Esophagoscopy–Induced Aortic Rupture During Oral Gastric Tube Placement in Patient With Esophageal Stricture: A Case Report. A&A Practice. 11(1). 14–15. 1 indexed citations
16.
Gabel, Eilon, Ira Hofer, Nancy Satou, et al.. (2017). Creation and Validation of an Automated Algorithm to Determine Postoperative Ventilator Requirements After Cardiac Surgery. Anesthesia & Analgesia. 124(5). 1423–1430. 12 indexed citations
17.
Young, Andrew, et al.. (2017). Preoperative risk stratification of critically ill patients. Journal of Clinical Anesthesia. 39. 122–127. 7 indexed citations
18.
Hofer, Ira, et al.. (2016). A Systematic Approach to Creation of a Perioperative Data Warehouse. Anesthesia & Analgesia. 122(6). 1880–1884. 55 indexed citations
19.
Gabel, Eilon, Vadim Gudzenko, Daniel Cruz, Abbas Ardehali, & Mitchell P. Fink. (2013). Successful Use of Extracorporeal Membrane Oxygenation in an Adult Patient With Toxic Shock-Induced Heart Failure. Journal of Intensive Care Medicine. 30(2). 115–118. 13 indexed citations
20.
Brautbar, Nachman, et al.. (2006). Occupational Kidney Cancer. Annals of the New York Academy of Sciences. 1076(1). 753–764. 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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