Andrew Bishara

737 total citations · 1 hit paper
17 papers, 458 citations indexed

About

Andrew Bishara is a scholar working on Cardiology and Cardiovascular Medicine, Surgery and Health Informatics. According to data from OpenAlex, Andrew Bishara has authored 17 papers receiving a total of 458 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Cardiology and Cardiovascular Medicine, 6 papers in Surgery and 3 papers in Health Informatics. Recurrent topics in Andrew Bishara's work include Cardiac, Anesthesia and Surgical Outcomes (6 papers), Machine Learning in Healthcare (3 papers) and Artificial Intelligence in Healthcare and Education (3 papers). Andrew Bishara is often cited by papers focused on Cardiac, Anesthesia and Surgical Outcomes (6 papers), Machine Learning in Healthcare (3 papers) and Artificial Intelligence in Healthcare and Education (3 papers). Andrew Bishara collaborates with scholars based in United States, Australia and Iran. Andrew Bishara's co-authors include Romain Pirracchio, Ivana Malenica, Rachael V. Phillips, Alan Hubbard, Jean Feng, Leo Anthony Celi, Jayakanth Srinivasan, Atul J. Butte, Donald T. Hess and Jonathan Woodson and has published in prestigious journals such as Intensive Care Medicine, Surgical Endoscopy and British Medical Bulletin.

In The Last Decade

Andrew Bishara

16 papers receiving 448 citations

Hit Papers

Clinical artificial intelligence quality improvement: tow... 2022 2026 2023 2024 2022 50 100 150
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.

  1. Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare
    2022 195 citations Jean Feng, Rachael V. Phillips et al. npj Digital Medicine profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andrew Bishara United States 8 154 114 111 104 91 17 458
Chris Giordano United States 9 124 0.8× 73 0.6× 117 1.1× 47 0.5× 113 1.2× 21 418
Kristin Corey United States 9 97 0.6× 116 1.0× 76 0.7× 71 0.7× 149 1.6× 20 516
Gina Barnes United States 13 78 0.5× 129 1.1× 44 0.4× 109 1.0× 28 0.3× 31 486
Jeremy A. Balch United States 13 86 0.6× 97 0.9× 63 0.6× 42 0.4× 83 0.9× 45 455
Prashant Warier United States 4 160 1.0× 216 1.9× 129 1.2× 290 2.8× 97 1.1× 5 845
Sehj Kashyap United States 6 117 0.8× 90 0.8× 66 0.6× 46 0.4× 53 0.6× 10 311
Mjaye Mazwi Canada 14 143 0.9× 110 1.0× 184 1.7× 54 0.5× 136 1.5× 51 724
Varun Buch United States 8 141 0.9× 132 1.2× 24 0.2× 152 1.5× 29 0.3× 11 423
Lovedeep Singh Dhingra United States 11 91 0.6× 54 0.5× 221 2.0× 71 0.7× 24 0.3× 36 428
Anthony Lin United States 7 82 0.5× 99 0.9× 38 0.3× 43 0.4× 33 0.4× 16 433

Countries citing papers authored by Andrew Bishara

Since Specialization
Citations

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

Fields of papers citing papers by Andrew Bishara

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrew Bishara

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

All Works

17 of 17 papers shown
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Chiu, Catherine, et al.. (2025). Development of a machine learning-derived model to predict unplanned ICU admissions after major non-cardiac surgery. BMC Anesthesiology. 25(1). 351–351. 1 indexed citations
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Feng, Jean, Rachael V. Phillips, Ivana Malenica, et al.. (2022). Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare. npj Digital Medicine. 5(1). 66–66. 195 indexed citations breakdown →
6.
Kothari, Rishi, Catherine Chiu, Andrew Bishara, et al.. (2022). A descriptive appraisal of quality of reporting in a cohort of machine learning studies in anesthesiology. Anaesthesia Critical Care & Pain Medicine. 41(5). 101126–101126. 2 indexed citations
7.
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Bishara, Andrew, Catherine Chiu, Elizabeth L. Whitlock, et al.. (2022). Postoperative delirium prediction using machine learning models and preoperative electronic health record data. BMC Anesthesiology. 22(1). 8–8. 56 indexed citations
9.
Panahiazar, Maryam, Andrew Bishara, Roohallah Alizadehsani, et al.. (2022). Gender-based time discrepancy in diagnosis of coronary artery disease based on data analytics of electronic medical records. Frontiers in Cardiovascular Medicine. 9. 969325–969325. 5 indexed citations
10.
Bishara, Andrew, et al.. (2022). Considerations for the implementation of machine learning into acute care settings. British Medical Bulletin. 141(1). 15–32. 3 indexed citations
11.
Bishara, Andrew, Andrew Wong, Nicholas Fong, et al.. (2021). Opal: an implementation science tool for machine learning clinical decision support in anesthesia. Journal of Clinical Monitoring and Computing. 36(5). 1367–1377. 11 indexed citations
12.
Bishara, Andrew, Dmytro Lituiev, Dieter Adelmann, et al.. (2021). Machine Learning Prediction of Liver Allograft Utilization From Deceased Organ Donors Using the National Donor Management Goals Registry. Transplantation Direct. 7(10). e771–e771. 5 indexed citations
13.
Alizadehsani, Roohallah, Abbas Khosravi, Mohamad Roshanzamir, et al.. (2020). Coronary artery disease detection using artificial intelligence techniques: A survey of trends, geographical differences and diagnostic features 1991–2020. Computers in Biology and Medicine. 128. 104095–104095. 77 indexed citations
14.
Bishara, Andrew, Susanna W.L. de Geus, Prasad Patil, et al.. (2020). Development and validation of machine learning models to predict gastrointestinal leak and venous thromboembolism after weight loss surgery: an analysis of the MBSAQIP database. Surgical Endoscopy. 35(1). 182–191. 61 indexed citations
15.
Legrand, Matthieu, Rachael V. Phillips, Ivana Malenica, et al.. (2020). Differences in clinical deterioration among three sub-phenotypes of COVID-19 patients at the time of first positive test: results from a clustering analysis. Intensive Care Medicine. 47(1). 113–115. 15 indexed citations
16.
Phipps, William S., Zhizhong Yin, Andrew Bishara, et al.. (2014). Reduced-gravity Environment Hardware Demonstrations of a Prototype Miniaturized Flow Cytometer and Companion Microfluidic Mixing Technology. Journal of Visualized Experiments. e51743–e51743. 7 indexed citations
17.
Phipps, William S., Zhizhong Yin, Andrew Bishara, et al.. (2014). Reduced-gravity Environment Hardware Demonstrations of a Prototype Miniaturized Flow Cytometer and Companion Microfluidic Mixing Technology. Journal of Visualized Experiments. 2 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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