Creating an Empirical Dermatology Dataset Through Crowdsourcing With Web Search Advertisements
The findings of this survey study suggest that search ads are effective at crowdsourcing dermatology images and could therefore be a useful method to create health datasets. The SCIN dataset bridges important gaps in the availability of images of common, short-duration skin conditions.
Authors
- Alan Karthikesalingam (ORCID: https://orcid.org/0000-0001-5074-898X)
- Jay Hartford
- Christopher Semturs (ORCID: https://orcid.org/0000-0001-6108-2773)
- Dawn H. Siegel (ORCID: https://orcid.org/0000-0001-6546-2693)
- Bilson Campana
- Justin Ko (ORCID: https://orcid.org/0000-0003-4232-5906)
- Sriram Lakshminarasimhan
- Julie Wang (ORCID: https://orcid.org/0000-0001-5956-0123)
- Sunny Virmani (ORCID: https://orcid.org/0009-0008-0647-8853)
- Steven Lin (ORCID: https://orcid.org/0000-0002-7542-4663)
- Dale R. Webster (ORCID: https://orcid.org/0000-0002-3023-8824)
- Renee Wong (ORCID: https://orcid.org/0009-0003-0403-7679)
- Yossi Matias (ORCID: https://orcid.org/0000-0003-3960-6002)
- Greg S. Corrado (ORCID: https://orcid.org/0000-0001-8817-0992)
- Ashley Carrick
- Pooja Rao
- Margaret A. Smith (ORCID: https://orcid.org/0000-0003-0052-7454)
- Jimmy Li (ORCID: https://orcid.org/0009-0004-8585-9347)
- Abbi Ward
- Pradeep K. Sreenivasaiah
- Tiya Tiyasirisokchai
Institutions
- Google (United States) (US)
- Stanford Health Care (US)
- Google (United Kingdom) (GB)
- Stanford University (US)
Publication Details
- Journal
- JAMA Network Open
- Published
- 2024-11-20
- DOI
- https://doi.org/10.1001/jamanetworkopen.2024.46615
- Citations
- 16
- Primary Topic
- Social Media in Health Education
- Type
- article
- Field-Weighted Citation Impact
- 8.45