Oishi Banerjee

4.0k total citations · 2 hit papers
7 papers, 2.2k citations indexed

About

Oishi Banerjee is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Informatics and Artificial Intelligence. According to data from OpenAlex, Oishi Banerjee has authored 7 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Radiology, Nuclear Medicine and Imaging, 5 papers in Health Informatics and 3 papers in Artificial Intelligence. Recurrent topics in Oishi Banerjee's work include Radiomics and Machine Learning in Medical Imaging (5 papers), Artificial Intelligence in Healthcare and Education (5 papers) and COVID-19 diagnosis using AI (2 papers). Oishi Banerjee is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (5 papers), Artificial Intelligence in Healthcare and Education (5 papers) and COVID-19 diagnosis using AI (2 papers). Oishi Banerjee collaborates with scholars based in United States, Canada and Australia. Oishi Banerjee's co-authors include Pranav Rajpurkar, Eric J. Topol, Emma Chen, Jure Leskovec, Michael Moor, Harlan M. Krumholz, Zahra Shakeri Hossein Abad, Tobias Salz, Alex Moehring and Nikhil Agarwal and has published in prestigious journals such as Nature, Nature Medicine and Scientific Data.

In The Last Decade

Oishi Banerjee

6 papers receiving 2.1k citations

Hit Papers

align trajectories

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.

AI in health and medicine

2022 1.3k citations Pranav Rajpurkar, Emma Chen et al. Nature Medicine profile →
Foundation models for generalist medical artificial intelligence

2023 738 citations Michael Moor, Oishi Banerjee et al. Nature profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Oishi Banerjee United States	5	912	773	687	201	171	7	2.2k
Dun Jack Fu United Kingdom	17	563 0.6×	498 0.6×	1.2k 1.7×	194 1.0×	140 0.8×	41	2.1k
Judy Wawira Gichoya United States	24	1.2k 1.3×	717 0.9×	1.1k 1.6×	351 1.7×	150 0.9×	158	2.4k
Hui Zhi China	2	1.1k 1.2×	714 0.9×	722 1.1×	225 1.1×	458 2.7×	5	2.5k
Fei Jiang United States	10	1.1k 1.2×	728 0.9×	792 1.2×	238 1.2×	458 2.7×	31	2.7k
Claire Cui United States	4	665 0.7×	921 1.2×	742 1.1×	299 1.5×	304 1.8×	9	2.4k
Siegfried K. Wagner United Kingdom	23	657 0.7×	606 0.8×	1.6k 2.3×	276 1.4×	180 1.1×	94	3.0k
Livia Faes United Kingdom	20	651 0.7×	579 0.7×	1.6k 2.3×	222 1.1×	170 1.0×	66	2.7k
Christoph Kern Germany	14	494 0.5×	449 0.6×	983 1.4×	158 0.8×	137 0.8×	36	1.8k
Dietmar Frey Germany	19	546 0.6×	522 0.7×	751 1.1×	215 1.1×	159 0.9×	59	2.5k
Emma Chen United States	7	593 0.7×	456 0.6×	414 0.6×	133 0.7×	133 0.8×	13	1.4k

Countries citing papers authored by Oishi Banerjee

Since Specialization

Citations

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

Fields of papers citing papers by Oishi Banerjee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Oishi Banerjee

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

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Moehring, Alex, Oishi Banerjee, Adam Jacobi, et al.. (2025). A Dataset for Understanding Radiologist-Artificial Intelligence Collaboration. Scientific Data. 12(1). 739–739.

2.

Yu, Feiyang, Alex Moehring, Oishi Banerjee, et al.. (2024). Heterogeneity and predictors of the effects of AI assistance on radiologists. Nature Medicine. 30(3). 837–849. 63 indexed citations

3.

Banerjee, Oishi, Agustina Saenz, Warren Clements, et al.. (2024). ReXamine-Global: A Framework for Uncovering Inconsistencies in Radiology Report Generation Metrics. PubMed. 30. 185–198. 2 indexed citations

4.

Moor, Michael, Oishi Banerjee, Zahra Shakeri Hossein Abad, et al.. (2023). Foundation models for generalist medical artificial intelligence. Nature. 616(7956). 259–265. 738 indexed citations breakdown →

5.

Saenz, Agustina, et al.. (2023). Autonomous AI systems in the face of liability, regulations and costs. npj Digital Medicine. 6(1). 185–185. 33 indexed citations

6.

Rajpurkar, Pranav, Emma Chen, Oishi Banerjee, & Eric J. Topol. (2022). AI in health and medicine. Nature Medicine. 28(1). 31–38. 1337 indexed citations breakdown →

7.

Ellsworth, William L., et al.. (2021). CheXtransfer: Performance and Parameter Efficiency of ImageNet Models for Chest X-Ray Interpretation. arXiv (Cornell University). 9 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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