Marian Johnson
This is a likely match — the affiliation was inferred from OpenAlex, ORCID, and web sources but has not been fully confirmed. Treat with appropriate caution.
Researcher
Also affiliated: University of North Carolina at Chapel Hill (1988); Gynecologic Oncology Group (2018); University of Louisville (2019); University of Kentucky (2016–2019); Augusta University (2023–2026); Markey Cancer Center (2020); Augusta University Health (2023–2025); Institute for Female Pelvic Medicine and Reconstructive Surgery (2019)
Faculty Researcher
Research Areas
Biomedical Subjects
Biography and Research Information
OverviewAI-generated summary
Marian Johnson's research focuses on gynecologic oncology, with recent publications exploring the impact of social determinants of health on cervical cancer survival and the assessment of ovarian recurrence risk using machine learning. Other work has examined nutritional factors influencing immunotherapy outcomes and the association between inflammatory markers and early recurrence in ovarian cancer patients. Johnson has also investigated potential treatments for chemotherapy-induced peripheral neuropathy and the presentation of rare conditions like vulvar angiomyxomas.
Her scholarship metrics include an h-index of 11, with 48 total publications and 393 citations. Johnson has collaborated with several colleagues at the University of Arkansas for Medical Sciences, including Janet L. Lukacs, Misty Koch, Elizabeth Shinn, and Cody Felty.
Metrics
- h-index: 11
- Publications: 48
- Citations: 395
Selected Publications
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P664: Comparative evaluation of an AI-based scanner-agnostic add-on utility versus conventional karyotyping software (2026)
Collaboration Network
Top Collaborators
- P664: Comparative evaluation of an AI-based scanner-agnostic add-on utility versus conventional karyotyping software
- P664: Comparative evaluation of an AI-based scanner-agnostic add-on utility versus conventional karyotyping software
- P664: Comparative evaluation of an AI-based scanner-agnostic add-on utility versus conventional karyotyping software
- P664: Comparative evaluation of an AI-based scanner-agnostic add-on utility versus conventional karyotyping software
- P664: Comparative evaluation of an AI-based scanner-agnostic add-on utility versus conventional karyotyping software
- P664: Comparative evaluation of an AI-based scanner-agnostic add-on utility versus conventional karyotyping software
- P664: Comparative evaluation of an AI-based scanner-agnostic add-on utility versus conventional karyotyping software
- P664: Comparative evaluation of an AI-based scanner-agnostic add-on utility versus conventional karyotyping software
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