Roxana Daneshjou

7.8k citations
111 papers · 4.7k · 10 hit papers · h-index 30

Impact in

Papers in

    • Artificial Intelligence in Healthcare and Education 63
    • Cutaneous Melanoma Detection and Management 25

Roxana Daneshjou

99 papers receiving 4.5k citations

Roxana Daneshjou's Hit Papers

The TRIPOD-LLM reporting guideline for studies using large language models 2025 · 232 citations
2320+4+9Years since publication200400600

Peers

Roxana Daneshjou
Comparison fields: 5 of 162
  • Health Informatics 1.8k
  • Pharmacology 329
  • Toxicology 178
  • Computational Theory and Mathematics 436
  • Health Information Management 226
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Wei-Qi Wei United States
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Citations per field
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Citations per year

Countries citing papers authored by Roxana Daneshjou

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authors

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.

Border = papers with Roxana Daneshjou Line = papers co-authored together Roxana Daneshjou links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 111 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Data-Driven Prediction of Drug Effects and Interactions
Hit paper breakdown →
2012699
2
How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals
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2021352
3
Disparities in dermatology AI performance on a diverse, curated clinical image set
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2022285
4
Lack of Transparency and Potential Bias in Artificial Intelligence Data Sets and Algorithms
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2021277
5
Large language models propagate race-based medicine
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2023271
6
Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update
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2024232
7
The TRIPOD-LLM reporting guideline for studies using large language models
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2025232
8 2013216
9
Large Language Models in Medicine: The Potentials and Pitfalls
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2024211
10 2011179
11 2021123
12
A scoping review of reporting gaps in FDA-approved AI medical devices
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2024100
13
An evaluation framework for clinical use of large language models in patient interaction tasks
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202594
14 202390
15 202479
16 202467
17 202366
18 201451
19 201250
20 201450

About Roxana Daneshjou

Roxana Daneshjou is a scholar working on Health Informatics, Oncology, Safety Research, Pharmacology and Artificial Intelligence, having authored 111 papers that have together received 4.7k indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (63 papers), Cutaneous Melanoma Detection and Management (25 papers), Ethics and Social Impacts of AI (12 papers), Pharmacogenetics and Drug Metabolism (8 papers), Genomics and Rare Diseases (6 papers), Explainable Artificial Intelligence (XAI) (4 papers), AI in cancer detection (4 papers) and Digital Imaging in Medicine (4 papers). The work is most often cited by research in Health Informatics (1.8k citations), Pharmacology (329 citations), Toxicology (178 citations), Computational Theory and Mathematics (436 citations) and Health Information Management (226 citations). Roxana Daneshjou has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Russ Biagio Altman, James Zou, Nicholas P. Tatonetti, Patrick Peiyong Ye, Veronica M. Rotemberg, Jesutofunmi A. Omiye, Jenna Lester, David Ouyang, Konrad J. Karczewski and Kevin Wu. Their work appears in journals such as Journal of Investigative Dermatology, npj Digital Medicine, 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.

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