Oishi Banerjee

4.0k citations
7 papers · 2.2k indexed · 2 hit papers · h-index 5
Topics
Radiomics and Machine Learning in Medical Imaging (5 papers)Artificial Intelligence in Healthcare and Education (5 papers)COVID-19 diagnosis using AI (2 papers)

In The Last Decade

Oishi Banerjee

6 papers receiving 2.1k citations

Hit Papers

AI in health and medicine2022202620232024202220234008001.2k

Peers

Oishi Banerjee
Comparison fields: 5 of 176
  • Health Informatics 912
  • Artificial Intelligence 773
  • Radiology, Nuclear Medicine and Imaging 687
  • Biomedical Engineering 201
  • Health Information Management 171
Replace Emma Chen with:
Emma Chen United States
Matthieu Komorowski United Kingdom
Volodymyr Kuleshov United States
Claire Cui United States
Dietmar Frey Germany
Livia Faes United Kingdom
Judy Wawira Gichoya United States
Siegfried K. Wagner United Kingdom
Dun Jack Fu United Kingdom
Alvin Rajkomar United States
Oishi Banerjee relative to Emma Chen United States Emma Chen's profile →
Citations per field
00.5×1.5×1.9×
Emma Chen · 1×
Citations per year

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

7 of 7 papers shown
#WorkIndexed citations
1 0
2 63
3 2
4
Foundation models for generalist medical artificial intelligencebreakdown →
738
5 33
6
AI in health and medicinebreakdown →
1337
7 9

About Oishi Banerjee

Oishi Banerjee is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Health Information Management, having authored 7 papers that have together received 2.2k indexed citations. Recurring topics across this 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). The work is most often cited by research in Health Informatics (912 citations), Health Information Management (171 citations) and Radiology, Nuclear Medicine and Imaging (687 citations). Oishi Banerjee has collaborated with scholars based in United States, Canada and Australia. Frequent co-authors include Pranav Rajpurkar, Eric J. Topol, Emma Chen, Jure Leskovec, Harlan M. Krumholz, Michael Moor, Zahra Shakeri Hossein Abad, Feiyang Yu, Tobias Salz and Alex Moehring. Their work appears in journals such as Nature, Nature Medicine and Scientific Data.

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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