Nishanth Arun
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
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- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
Papers in
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- COVID-19 diagnosis using AI 2
- Radiomics and Machine Learning in Medical Imaging 1
- Retinal Imaging and Analysis 1
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- Tuberculosis Research and Epidemiology 1
- Co-authors
- Praveer Singh (6 shared papers)Jayashree Kalpathy–Cramer (6 shared papers)Ken Chang (4 shared papers)Mishka Gidwani (3 shared papers)Matthew Li (3 shared papers)Katharina Hoebel (3 shared papers)Nathan Gaw (2 shared papers)Sharut Gupta (3 shared papers)
- Journals
- Radiology Artificial Intelligence (2 papers)Investigative Ophthalmology & Visual Science (1 paper)Medicine (1 paper)Journal of the American College of Radiology (1 paper)Lecture notes in computer science (1 paper)
- Partner nations
- United StatesIndiaBrazil
In The Last Decade
Nishanth Arun
7 papers receiving 342 citations
Nishanth Arun's Hit Papers
Peers
Comparison fields: 5 of 61
- Health Informatics 72
- Radiology, Nuclear Medicine and Imaging 196
- Artificial Intelligence 125
- Health Information Management 7
- Biophysics 9
Countries citing papers authored by Nishanth Arun
This map shows the geographic impact of Nishanth Arun'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 Nishanth Arun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nishanth Arun more than expected).
Fields of papers citing papers by Nishanth Arun
This network shows the impact of papers produced by Nishanth Arun. 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 Nishanth Arun. The network helps show where Nishanth Arun may publish in the future.
Co-authors
The 25 scholars most cited alongside Nishanth Arun, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Assessing the Trustworthiness of Saliency Maps for Localizing Abnormalities in Medical Imaging Hit paper breakdown → | 2021 | 179 |
| 2 | 2020 | 110 | |
| 3 | 2020 | 39 | |
| 4 | 2022 | 10 | |
| 5 | 2021 | 7 | |
| 6 | Automated detection of genetic relatedness from fundus photographs using Convolutional Siamese Neural Networks | 2021 | 1 |
| 7 | 2025 | 1 | |
| 8 | 2025 | 0 |
About Nishanth Arun
Nishanth Arun is a scholar working on Radiology, Nuclear Medicine and Imaging, Infectious Diseases, Computer Networks and Communications, Genetics and Information Systems, having authored 8 papers that have together received 347 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Hepatocellular Carcinoma Treatment and Prognosis (1 paper), Tuberculosis Research and Epidemiology (1 paper), Retinal Imaging and Analysis (1 paper), Pneumonia and Respiratory Infections (1 paper), Glioma Diagnosis and Treatment (1 paper) and Advanced Malware Detection Techniques (1 paper). The work is most often cited by research in Health Informatics (72 citations), Radiology, Nuclear Medicine and Imaging (196 citations), Artificial Intelligence (125 citations), Health Information Management (7 citations) and Biophysics (9 citations). Nishanth Arun has collaborated with scholars based in United States, India and Brazil. Frequent co-authors include Praveer Singh, Jayashree Kalpathy–Cramer, Ken Chang, Mishka Gidwani, Matthew Li, Katharina Hoebel, Nathan Gaw, Sharut Gupta, Mehak Aggarwal and Julius Adebayo. Their work appears in journals such as Radiology Artificial Intelligence, Investigative Ophthalmology & Visual Science, Medicine, Journal of the American College of Radiology and Lecture notes in computer science.
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.