Melissa Davis

1.2k total citations
48 papers, 730 citations indexed

About

Melissa Davis is a scholar working on Radiology, Nuclear Medicine and Imaging, Pediatrics, Perinatology and Child Health and Health Informatics. According to data from OpenAlex, Melissa Davis has authored 48 papers receiving a total of 730 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Radiology, Nuclear Medicine and Imaging, 13 papers in Pediatrics, Perinatology and Child Health and 9 papers in Health Informatics. Recurrent topics in Melissa Davis's work include Radiology practices and education (14 papers), Birth, Development, and Health (12 papers) and Artificial Intelligence in Healthcare and Education (9 papers). Melissa Davis is often cited by papers focused on Radiology practices and education (14 papers), Birth, Development, and Health (12 papers) and Artificial Intelligence in Healthcare and Education (9 papers). Melissa Davis collaborates with scholars based in United States, Canada and United Kingdom. Melissa Davis's co-authors include Sean W. Limesand, Miranda J. Anderson, Vahe M. Zohrabian, Howard P. Forman, Kanhai Amin, Leticia E. Camacho, Amy C. Kelly, Orlando Gómez-Marı́n, Mario Sofer and Mark S. Soloway and has published in prestigious journals such as The Journal of Physiology, Radiology and Endocrinology.

In The Last Decade

Melissa Davis

42 papers receiving 716 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Melissa Davis United States 17 232 198 126 120 95 48 730
Maria Lourdes Gonzalez Suarez United States 15 91 0.4× 63 0.3× 104 0.8× 60 0.5× 91 1.0× 40 836
Seok‐Jae Heo South Korea 15 36 0.2× 97 0.5× 20 0.2× 12 0.1× 80 0.8× 78 658
Jami C. Levine United States 22 168 0.7× 117 0.6× 48 0.4× 35 0.3× 686 7.2× 50 1.8k
Joseph B. Leader United States 13 22 0.1× 88 0.4× 20 0.2× 18 0.1× 112 1.2× 23 748
Ziren Tang China 12 40 0.2× 38 0.2× 25 0.2× 9 0.1× 27 0.3× 40 631
Anthony Lin United States 7 59 0.3× 43 0.2× 6 0.0× 82 0.7× 33 0.3× 16 433
Jiyu Sun South Korea 14 43 0.2× 60 0.3× 62 0.5× 3 0.0× 71 0.7× 26 504
Murilo Foppa Brazil 17 29 0.1× 554 2.8× 11 0.1× 22 0.2× 293 3.1× 76 1.7k
Hee‐Jung Chung South Korea 12 64 0.3× 27 0.1× 41 0.3× 6 0.1× 59 0.6× 38 439
Sukrit Narula United States 13 11 0.0× 218 1.1× 7 0.1× 84 0.7× 125 1.3× 19 829

Countries citing papers authored by Melissa Davis

Since Specialization
Citations

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

Fields of papers citing papers by Melissa Davis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Melissa Davis

This figure shows the co-authorship network connecting the top 25 collaborators of Melissa Davis. A scholar is included among the top collaborators of Melissa Davis 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 Melissa Davis. Melissa Davis 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.
Czerminski, Jan T., et al.. (2024). The disproportionate impact of peer learning on emergency radiology. Emergency Radiology. 31(2). 133–139.
2.
Amin, Kanhai, et al.. (2024). Increasing patient viewership of complex imaging reports: The paradox of the Cures Act. Clinical Imaging. 119. 110398–110398.
3.
Amin, Kanhai, et al.. (2024). Release of complex imaging reports to patients, do radiologists trust AI to help?. Current Problems in Diagnostic Radiology. 54(2). 147–150. 3 indexed citations
4.
Ball, Robyn L., Luciano M. Prevedello, Ferco H. Berger, et al.. (2024). RSNA 2023 Abdominal Trauma AI Challenge: Review and Outcomes. Radiology Artificial Intelligence. 7(1). e240334–e240334. 1 indexed citations
5.
Unberath, Mathias, Guang Li, Melissa Davis, et al.. (2024). An ASER AI/ML expert panel formative user research study for an interpretable interactive splenic AAST grading graphical user interface prototype. Emergency Radiology. 31(2). 167–178. 6 indexed citations
6.
Amin, Kanhai, Howard P. Forman, & Melissa Davis. (2024). Even with ChatGPT, race matters. Clinical Imaging. 109. 110113–110113. 22 indexed citations
7.
Bahl, Manisha, Patricia Balthazar, Melissa Davis, et al.. (2024). ChatGPT and Large Language Models in Radiology: Perspectives From the Field. American Journal of Roentgenology. 223(4). e2432022–e2432022. 2 indexed citations
8.
Amin, Kanhai, Melissa Davis, Rushabh Doshi, et al.. (2023). Accuracy of ChatGPT, Google Bard, and Microsoft Bing for Simplifying Radiology Reports. Radiology. 309(2). e232561–e232561. 60 indexed citations
9.
Davis, Melissa, Ona Wu, Ichiro Ikuta, et al.. (2023). Understanding Bias in Artificial Intelligence: A Practice Perspective. American Journal of Neuroradiology. 45(4). 371–373. 2 indexed citations
10.
Abraham, Peter, et al.. (2023). Change Management Strategies Toward Dismantling Race-Based Structural Barriers in Radiology. Academic Radiology. 30(4). 658–665. 4 indexed citations
11.
Davis, Melissa, Cydney H. Dupree, & Carolyn C. Meltzer. (2022). Diversity, Equity, and Inclusion Efforts Are Organizational Change Management Efforts. Journal of the American College of Radiology. 19(1). 181–183. 5 indexed citations
12.
Banerjee, Imon, et al.. (2022). Natural Language Processing Model for Identifying Critical Findings—A Multi-Institutional Study. Journal of Digital Imaging. 36(1). 105–113. 11 indexed citations
13.
Zohrabian, Vahe M., et al.. (2020). Utility of Artificial Intelligence Tool as a Prospective Radiology Peer Reviewer — Detection of Unreported Intracranial Hemorrhage. Academic Radiology. 28(1). 85–93. 60 indexed citations
14.
Davis, Melissa, et al.. (2020). Machine Learning and Improved Quality Metrics in Acute Intracranial Hemorrhage by Noncontrast Computed Tomography. Current Problems in Diagnostic Radiology. 51(4). 556–561. 40 indexed citations
15.
Davis, Melissa, et al.. (2020). Trends in Publicly Reported Quality Measures of Hospital Imaging Efficiency, 2011–2018. American Journal of Roentgenology. 215(1). 153–158. 2 indexed citations
16.
Brown, Laura D., Melissa Davis, Stephanie R. Wesolowski, et al.. (2016). Chronically Increased Amino Acids Improve Insulin Secretion, Pancreatic Vascularity, and Islet Size in Growth-Restricted Fetal Sheep. Endocrinology. 157(10). 3788–3799. 31 indexed citations
17.
Davis, Melissa, et al.. (2011). Imaging the pregnant patient with abdominal pain. Abdominal Radiology. 37(5). 849–860. 17 indexed citations
18.
Davis, Melissa & James G. Ravenel. (2008). Paraneoplastic Limbic Encephalitis due to Thymic Carcinoid. Journal of Thoracic Oncology. 3(12). 1484–1486. 3 indexed citations
19.
Spampinato, Maria Vittoria, et al.. (2008). Thrombosed Fetal Dural Sinus Malformation Diagnosed With Magnetic Resonance Imaging. Obstetrics and Gynecology. 111(2). 569–572. 19 indexed citations
20.
Davis, Melissa, et al.. (2003). The use of cell salvage during radical retropubic prostatectomy: does it influence cancer recurrence?. British Journal of Urology. 91(6). 474–476. 59 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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