Shruthi Bannur

658 total citations
7 papers, 148 citations indexed

About

Shruthi Bannur is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Shruthi Bannur has authored 7 papers receiving a total of 148 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 3 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Shruthi Bannur's work include Radiomics and Machine Learning in Medical Imaging (3 papers), Topic Modeling (3 papers) and Machine Learning in Healthcare (2 papers). Shruthi Bannur is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (3 papers), Topic Modeling (3 papers) and Machine Learning in Healthcare (2 papers). Shruthi Bannur collaborates with scholars based in United States, United Kingdom and India. Shruthi Bannur's co-authors include Daniel C. Castro, Ozan Oktay, Anton Schwaighofer, Matthew P. Lungren, Javier Alvarez-Valle, Aditya Nori, Fernando Pérez‐García, Harshita Sharma, Stephanie L. Hyland and Kerem Can Tezcan and has published in prestigious journals such as Nature Communications, International Journal of Medical Informatics and Nature Machine Intelligence.

In The Last Decade

Shruthi Bannur

6 papers receiving 143 citations

Peers

Shruthi Bannur

AI

RNMI

CVPR

HI

MB

Javier Alvarez-Valle United States

Maximilian Ilse Netherlands

Tobias Roß Germany

Alina Jade Barnett United States

Anees Kazi Germany

Annika Reinke Germany

Jungkyu Park United States

Weidi Xie China

Youssef Skandarani Canada

Javier Alvarez-Valle United States

Shruthi Bannur

106 ×1.2

AI

97 ×1.8

RNMI

39 ×1.1

CVPR

48 ×1.5

HI

13 ×1.0

MB

Citations per year, relative to Shruthi Bannur Shruthi Bannur (= 1×) peers Javier Alvarez-Valle

Countries citing papers authored by Shruthi Bannur

Since Specialization

Citations

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

Fields of papers citing papers by Shruthi Bannur

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shruthi Bannur

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

All Works

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7 of 7 papers shown

1.

Kumar, Vaibhav, et al.. (2025). Development and application of DAISY framework for benchmarking AI generated vs human-written abstracts in dental research. International Journal of Medical Informatics. 207. 106190–106190.

2.

Pérez‐García, Fernando, Harshita Sharma, Valentina Salvatelli, et al.. (2025). Exploring scalable medical image encoders beyond text supervision. Nature Machine Intelligence. 7(1). 119–130. 11 indexed citations

3.

Pérez‐García, Fernando, Shruthi Bannur, Daniel C. Castro, et al.. (2024). MAIRA at RRG24: A specialised large multimodal model for radiology report generation. 597–602. 4 indexed citations

4.

Liu, Qianchu, Stephanie L. Hyland, Shruthi Bannur, et al.. (2023). Exploring the Boundaries of GPT-4 in Radiology. 14414–14445. 14 indexed citations

5.

Liu, Fangyu, Qianchu Liu, Shruthi Bannur, et al.. (2023). Compositional Zero-Shot Domain Transfer with Text-to-Text Models. Transactions of the Association for Computational Linguistics. 11. 1097–1113. 2 indexed citations

6.

Bannur, Shruthi, Stephanie L. Hyland, Qianchu Liu, et al.. (2023). Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing. 15016–15027. 62 indexed citations

7.

Castro, Daniel C., Ryutaro Tanno, Anton Schwaighofer, et al.. (2022). Active label cleaning for improved dataset quality under resource constraints. Nature Communications. 13(1). 1161–1161. 55 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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