Mohith Shamdas
Impact in
- Health Informatics top 0.1%
- Artificial Intelligence in Healthcare and Education
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- Artificial Intelligence in Healthcare
Papers in
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- Ocular Diseases and Behçet’s Syndrome 3
- Retinal and Optic Conditions 2
- Retinal Diseases and Treatments 1
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- Dermatology and Skin Diseases 2
- Co-authors
- Alastair K. Denniston (3 shared papers)Martin Schmid (2 shared papers)Livia Faes (2 shared papers)Alice Bruynseels (2 shared papers)Gabriella Moraes (2 shared papers)Xiaoxuan Liu (2 shared papers)Siegfried K. Wagner (2 shared papers)Aditya U. Kale (2 shared papers)
- Journals
- Ocular Immunology and Inflammation (2 papers)BMC Ophthalmology (1 paper)British Journal of Ophthalmology (1 paper)The Lancet Digital Health (1 paper)The Clinical Teacher (1 paper)
- Partner nations
- United KingdomSwitzerlandUnited States
In The Last Decade
Mohith Shamdas
10 papers receiving 1.2k citations
Mohith Shamdas's Hit Papers
Peers
Comparison fields: 5 of 127
- Health Informatics 452
- Health Information Management 93
- Radiology, Nuclear Medicine and Imaging 399
- Family Practice 18
- Artificial Intelligence 345
Countries citing papers authored by Mohith Shamdas
This map shows the geographic impact of Mohith Shamdas'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 Mohith Shamdas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohith Shamdas more than expected).
Fields of papers citing papers by Mohith Shamdas
This network shows the impact of papers produced by Mohith Shamdas. 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 Mohith Shamdas. The network helps show where Mohith Shamdas may publish in the future.
Co-authors
The 25 scholars most cited alongside Mohith Shamdas, 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 | A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis Hit paper breakdown → | 2019 | 1163 |
| 2 | 2018 | 18 | |
| 3 | 2022 | 18 | |
| 4 | 2019 | 14 | |
| 5 | 2019 | 8 | |
| 6 | 2022 | 7 | |
| 7 | 2020 | 4 | |
| 8 | 2020 | 2 | |
| 9 | Conjunctivitis due to Dupilumab Treatment in Atopic Dermatitis: Clinical features and impact on gut microbiome | 2019 | 1 |
| 10 | 2015 | 1 |
About Mohith Shamdas
Mohith Shamdas is a scholar working on Ophthalmology, Dermatology, Radiology, Nuclear Medicine and Imaging, Molecular Biology and Pathology and Forensic Medicine, having authored 10 papers that have together received 1.2k indexed citations. Recurring topics across this work include Ocular Diseases and Behçet’s Syndrome (3 papers), Retinal and Optic Conditions (2 papers), Dermatology and Skin Diseases (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Retinal Diseases and Treatments (1 paper), Hair Growth and Disorders (1 paper), Autoimmune Bullous Skin Diseases (1 paper) and Gut microbiota and health (1 paper). The work is most often cited by research in Health Informatics (452 citations), Health Information Management (93 citations), Radiology, Nuclear Medicine and Imaging (399 citations), Family Practice (18 citations) and Artificial Intelligence (345 citations). Mohith Shamdas has collaborated with scholars based in United Kingdom, Switzerland and United States. Frequent co-authors include Alastair K. Denniston, Martin Schmid, Livia Faes, Alice Bruynseels, Gabriella Moraes, Xiaoxuan Liu, Siegfried K. Wagner, Aditya U. Kale, Eric J. Topol and Lucas M. Bachmann. Their work appears in journals such as Ocular Immunology and Inflammation, BMC Ophthalmology, British Journal of Ophthalmology, The Lancet Digital Health and The Clinical Teacher.
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.