Veronica Rotemberg

73 papers receiving 1.5k citations

Veronica Rotemberg's Hit Papers

Large language models propagate race-based medicine 2023 · 212 citations
2120+1+3Years since publication50100150200

Peers

Veronica Rotemberg
Comparison fields: 5 of 146
  • Health Informatics 275
  • Oncology 532
  • Dermatology 154
  • Radiology, Nuclear Medicine and Imaging 287
  • Artificial Intelligence 326
Replace Adewole S. Adamson with:
Adewole S. Adamson United States
Christine Fink Germany
Titus J. Brinker Germany
Alan Roger Santos‐Silva Brazil
Sachin C. Sarode India
Jessica W. T. Leung United States
Sanjay Aneja United States
Lars J. Grimm United States
Shelly Soffer Israel
William Parker Canada
Veronica Rotemberg relative to Adewole S. Adamson United States Adewole S. Adamson's profile →
Citations per field
00.5×3.9×
Adewole S. Adamson · 1×
Citations per year

Countries citing papers authored by Veronica Rotemberg

Since Specialization
Citations

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

Fields of papers citing papers by Veronica Rotemberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Veronica Rotemberg, 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 Veronica Rotemberg Line = papers co-authored together Veronica Rotemberg links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 83 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Lack of Transparency and Potential Bias in Artificial Intelligence Data Sets and Algorithms
Hit paper breakdown →
2021217
2
Large language models propagate race-based medicine
Hit paper breakdown →
2023212
3 2010104
4 202199
5 202281
6 202357
7 202454
8 201453
9 202345
10 202442
11 202141
12 201938
13 201837
14 201134
15 202328
16 202424
17 202220
18 201819
19 202119
20 201318

About Veronica Rotemberg

Veronica Rotemberg is a scholar working on Oncology, Artificial Intelligence, Dermatology, Epidemiology and Physiology, having authored 83 papers that have together received 1.6k indexed citations. Recurring topics across this work include Cutaneous Melanoma Detection and Management (35 papers), AI in cancer detection (13 papers), Ultrasound Imaging and Elastography (7 papers), Digital Imaging in Medicine (6 papers), Ultrasound and Hyperthermia Applications (5 papers), Histiocytic Disorders and Treatments (5 papers), Nonmelanoma Skin Cancer Studies (5 papers) and Artificial Intelligence in Healthcare and Education (5 papers). The work is most often cited by research in Health Informatics (275 citations), Oncology (532 citations), Dermatology (154 citations), Radiology, Nuclear Medicine and Imaging (287 citations) and Artificial Intelligence (326 citations). Veronica Rotemberg has collaborated with scholars based in United States, Australia and Spain. Frequent co-authors include Roxana Daneshjou, Mary Sun, James Zou, Mark L. Palmeri, Jenna Lester, Jesutofunmi A. Omiye, Simon Spichak, Allan C. Halpern, Kathryn R. Nightingale and Ned C. Rouze. Their work appears in journals such as Journal of the American Academy of Dermatology, npj Digital Medicine, Journal of the European Academy of Dermatology and Venereology, Journal of Investigative Dermatology and JAMA 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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