Automated Detection of Kaposi Sarcoma–Associated Herpesvirus–Infected Cells in Immunohistochemical Images of Skin Biopsies
The framework shows promise for the automated detection of LANA in skin biopsies, offering a reliable and accurate tool for identifying anti-LANA-positive cells. This method may be especially impactful in resource-limited areas that lack trained pathologists, potentially improving diagnostic capabilities in settings with limited access to expert analysis.
Authors
- Aggrey Semeere (ORCID: https://orcid.org/0000-0003-1826-2239)
- Jeffrey N. Martin (ORCID: https://orcid.org/0000-0002-9773-3256)
- Robert Lukande (ORCID: https://orcid.org/0000-0001-9449-6649)
- Racheal Ayanga (ORCID: https://orcid.org/0000-0002-6726-6300)
- Toby Maurer (ORCID: https://orcid.org/0000-0003-1968-3916)
- David Erickson (ORCID: https://orcid.org/0000-0002-1624-9711)
- Iftak Hussain (ORCID: https://orcid.org/0000-0001-7469-4314)
- Ethel Cesarman (ORCID: https://orcid.org/0000-0003-3303-6299)
- Juan Boza (ORCID: https://orcid.org/0000-0001-8153-9371)
Institutions
- University of California, San Francisco (US)
- Cornell University (US)
- Infectious Diseases Institute (UG)
- Indiana University School of Medicine
- Indiana University – Purdue University Indianapolis (US)
- Makerere University (UG)
Publication Details
- Journal
- JCO Global Oncology
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1200/go-24-00536
- Primary Topic
- Viral-associated cancers and disorders
- Type
- article
- Field-Weighted Citation Impact
- 0.00