Bernardo C. Bizzo

2.4k total citations
59 papers, 880 citations indexed

About

Bernardo C. Bizzo is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Bernardo C. Bizzo has authored 59 papers receiving a total of 880 indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Radiology, Nuclear Medicine and Imaging, 18 papers in Biomedical Engineering and 16 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Bernardo C. Bizzo's work include Radiomics and Machine Learning in Medical Imaging (17 papers), Radiology practices and education (16 papers) and Advanced X-ray and CT Imaging (14 papers). Bernardo C. Bizzo is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (17 papers), Radiology practices and education (16 papers) and Advanced X-ray and CT Imaging (14 papers). Bernardo C. Bizzo collaborates with scholars based in United States, Brazil and Iran. Bernardo C. Bizzo's co-authors include Mannudeep K. Kalra, Keith J. Dreyer, Tarik K. Alkasab, Shadi Ebrahimian, Renata R. Almeida, Mark Michalski, Subba R. Digumarthy, Bibb Allen, Katherine P. Andriole and James Hillis and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Stroke.

In The Last Decade

Bernardo C. Bizzo

54 papers receiving 867 citations

Peers

Bernardo C. Bizzo

RNMI

PRM

Jaron Chong Canada

Sirish Shrestha United States

Thomas Weikert Switzerland

Ju Gang Nam South Korea

Elizabeth Le United Kingdom

Joshy Cyriac Switzerland

Youngbin Shin South Korea

Jeremy R. Burt United States

Hye Young Jang South Korea

Bardia Khosravi United States

Jaron Chong Canada

Bernardo C. Bizzo

649 ×1.2

RNMI

293 ×1.1

176 ×0.8

136 ×0.9

PRM

209 ×1.5

Citations per year, relative to Bernardo C. Bizzo Bernardo C. Bizzo (= 1×) peers Jaron Chong

Countries citing papers authored by Bernardo C. Bizzo

Since Specialization

Citations

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

Fields of papers citing papers by Bernardo C. Bizzo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bernardo C. Bizzo

This figure shows the co-authorship network connecting the top 25 collaborators of Bernardo C. Bizzo. A scholar is included among the top collaborators of Bernardo C. Bizzo 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 Bernardo C. Bizzo. Bernardo C. Bizzo 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

Tripathi, Satvik, Azadeh Tabari, Bernardo C. Bizzo, et al.. (2025). PRECISE framework: Enhanced radiology reporting with GPT for improved readability, reliability, and patient-centered care. European Journal of Radiology. 187. 112124–112124. 1 indexed citations

Mercaldo, Sarah, Sandeep Hedgire, Nandini M. Meyersohn, et al.. (2025). Evaluation of an artificial intelligence model for opportunistic Agatston scoring on non-gated chest computed tomography. Scientific Reports. 15(1). 39535–39535.

Bizzo, Bernardo C., et al.. (2025). Regulating Generative AI in Radiology Practice: A Trilaminar Approach to Balancing Risk with Innovation. Academic Radiology. 32(9). 4965–4973.

Karout, Lina, et al.. (2024). Early Detection of Heart Failure with Autonomous AI-Based Model Using Chest Radiographs: A Multicenter Study. Diagnostics. 14(15). 1635–1635. 2 indexed citations

Buch, Karen, John Conklin, William A. Mehan, et al.. (2024). Evaluation of an Artificial Intelligence Model for Identification of Mass Effect and Vasogenic Edema on CT of the Head. American Journal of Neuroradiology. 45(10). 1528–1535. 1 indexed citations

Hillis, James, Sarah Mercaldo, Subba R. Digumarthy, et al.. (2024). The Potential Clinical Utility of an Artificial Intelligence Model for Identification of Vertebral Compression Fractures in Chest Radiographs. Journal of the American College of Radiology. 22(2). 220–229. 1 indexed citations

Bizzo, Bernardo C., et al.. (2024). Assessing Laterality Errors in Radiology: Comparing Generative Artificial Intelligence and Natural Language Processing. Journal of the American College of Radiology. 21(10). 1575–1582. 5 indexed citations

Li, Matthew, Nishanth Arun, Mehak Aggarwal, et al.. (2022). Multi-population generalizability of a deep learning-based chest radiograph severity score for COVID-19. Medicine. 101(29). e29587–e29587. 10 indexed citations

Patel, Jay, Bernardo C. Bizzo, Daniel I. Glazer, et al.. (2022). Machine Learning for Adrenal Gland Segmentation and Classification of Normal and Adrenal Masses at CT. Radiology. 306(2). e220101–e220101. 23 indexed citations

10.

Daye, Dania, Walter F. Wiggins, Matthew P. Lungren, et al.. (2022). Implementation of Clinical Artificial Intelligence in Radiology: Who Decides and How?. Radiology. 305(3). 555–563. 70 indexed citations

11.

Ebrahimian, Shadi, Subba R. Digumarthy, Fatemeh Homayounieh, et al.. (2022). Predictive values of AI-based triage model in suboptimal CT pulmonary angiography. Clinical Imaging. 86. 25–30. 9 indexed citations

12.

Bizzo, Bernardo C., Shadi Ebrahimian, Mark Michalski, et al.. (2022). Validation pipeline for machine learning algorithm assessment for multiple vendors. PLoS ONE. 17(4). e0267213–e0267213. 2 indexed citations

13.

Zhong, Aoxiao, Xiang Li, Dufan Wu, et al.. (2021). Deep metric learning-based image retrieval system for chest radiograph and its clinical applications in COVID-19. Medical Image Analysis. 70. 101993–101993. 51 indexed citations

14.

Ebrahimian, Shadi, Fatemeh Homayounieh, Marcio Aloísio Bezerra Cavalcanti Rockenbach, et al.. (2021). Artificial intelligence matches subjective severity assessment of pneumonia for prediction of patient outcome and need for mechanical ventilation: a cohort study. Scientific Reports. 11(1). 858–858. 30 indexed citations

15.

Bizzo, Bernardo C., Renata R. Almeida, & Tarik K. Alkasab. (2021). Data Management in Artificial Intelligence–Assisted Radiology Reporting. Journal of the American College of Radiology. 18(11). 1485–1488. 2 indexed citations

16.

Homayounieh, Fatemeh, Marcio Aloísio Bezerra Cavalcanti Rockenbach, Shadi Ebrahimian, et al.. (2021). Multicenter Assessment of CT Pneumonia Analysis Prototype for Predicting Disease Severity and Patient Outcome. Journal of Digital Imaging. 34(2). 320–329. 9 indexed citations

17.

Alkasab, Tarik K. & Bernardo C. Bizzo. (2021). Lessons Learned From the Front Lines of Artificial Intelligence Implementation. Journal of the American College of Radiology. 18(11). 1474–1475. 1 indexed citations

18.

Bizzo, Bernardo C., Renata R. Almeida, & Tarik K. Alkasab. (2021). Artificial Intelligence Enabling Radiology Reporting. Radiologic Clinics of North America. 59(6). 1045–1052. 12 indexed citations

19.

Ebrahimian, Shadi, Mannudeep K. Kalra, Sheela Agarwal, et al.. (2021). FDA-regulated AI Algorithms: Trends, Strengths, and Gaps of Validation Studies. Academic Radiology. 29(4). 559–566. 81 indexed citations

20.

Homayounieh, Fatemeh, Shadi Ebrahimian, Rosa Babaei, et al.. (2020). CT Radiomics, Radiologists, and Clinical Information in Predicting Outcome of Patients with COVID-19 Pneumonia. Radiology Cardiothoracic Imaging. 2(4). e200322–e200322. 42 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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