Roxana Daneshjou
- Health Informatics top 0.05%
- Artificial Intelligence in Healthcare and Education 23
- Toxicology top 1%
- Pharmacology top 2%
- Pharmacogenetics and Drug Metabolism 7
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- Cutaneous Melanoma Detection and Management 27
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- AI in cancer detection 18
- Machine Learning in Healthcare 7
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- Digital Imaging in Medicine 8
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- Genetic Associations and Epidemiology 5
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- Social Media in Health Education 5
- Co-authors
- Russ B. AltmanNicholas P. TatonettiJames ZouVeronica RotembergJesutofunmi A. OmiyeDavid OuyangKonrad J. KarczewskiDaniel E. Ho
- Journals
- npj Digital Medicine (8 papers)Journal of Investigative Dermatology (7 papers)JAMA Dermatology (7 papers)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Roxana Daneshjou
65 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 171
- Health Informatics 690
- Toxicology 161
- Computational Theory and Mathematics 482
- Pharmacology 224
- Health Information Management 113
Countries citing papers authored by Roxana Daneshjou
This map shows the geographic impact of Roxana Daneshjou'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 Roxana Daneshjou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roxana Daneshjou more than expected).
Fields of papers citing papers by Roxana Daneshjou
This network shows the impact of papers produced by Roxana Daneshjou. 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 Roxana Daneshjou. The network helps show where Roxana Daneshjou may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Roxana Daneshjou, 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 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 0 | |
| 5 | 2024 | 0 | |
| 6 | 2024 | 2 | |
| 7 | Large Language Models in Medicine: The Potentials and Pitfallsbreakdown → | 2024 | 131 |
| 8 | 2024 | 58 | |
| 9 | 2024 | 48 | |
| 10 | 2024 | 10 | |
| 11 | 2024 | 1 | |
| 12 | 2024 | 36 | |
| 13 | 2023 | 27 | |
| 14 | 2023 | 12 | |
| 15 | 2023 | 42 | |
| 16 | 2023 | 64 | |
| 17 | Lack of Transparency and Potential Bias in Artificial Intelligence Data Sets and Algorithmsbreakdown → | 2021 | 198 |
| 18 | 2021 | 5 | |
| 19 | 2020 | 16 | |
| 20 | 2017 | 8 |
About Roxana Daneshjou
Roxana Daneshjou is a scholar working on Health Informatics, Family Practice, Oncology, Artificial Intelligence and Pharmacology, having authored 77 papers that have together received 2.6k indexed citations. Recurring topics across this work include Cutaneous Melanoma Detection and Management (27 papers), Artificial Intelligence in Healthcare and Education (23 papers), AI in cancer detection (18 papers), Digital Imaging in Medicine (8 papers), Pharmacogenetics and Drug Metabolism (7 papers), Machine Learning in Healthcare (7 papers), Genetic Associations and Epidemiology (5 papers) and Social Media in Health Education (5 papers). The work is most often cited by research in Health Informatics (690 citations), Toxicology (161 citations), Computational Theory and Mathematics (482 citations), Pharmacology (224 citations) and Health Information Management (113 citations). Roxana Daneshjou has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Russ B. Altman, Nicholas P. Tatonetti, James Zou, Veronica Rotemberg, Jesutofunmi A. Omiye, David Ouyang, Konrad J. Karczewski, Daniel E. Ho, Kevin Wu and Eric Q. Wu. Their work appears in journals such as npj Digital Medicine, Journal of Investigative Dermatology, JAMA Dermatology, Nature Medicine and Journal of the American Academy of Dermatology.
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.