Publications
53
Citations
271
Est. group size
~10
Recurring co-author estimate
Active years
14
Publishing since 2013
Vincent Wagner's research focuses on gynecologic cancers, particularly endometrial and ovarian cancer, with an emphasis on using artificial intelligence and machine learning to improve diagnosis, subtyping, and prediction of treatment outcomes. His work combines analysis of histopathology images (tissue slides viewed under a microscope), genomic and DNA methylation data, and imaging scans (like CT) to help identify cancer subtypes and predict how likely a cancer is to recur or respond to chemotherapy. He also studies clinical risk factors such as venous thromboembolism (blood clots) in cancer patients and has contributed to leadership training programs for gynecologic oncology fellows.
Publication output has grown substantially over the last decade, rising from a few papers per year in the late 2010s to a peak of 13 in 2025, indicating an increasing and active research pace.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Real-world benchmarking and validation of foundation model transformers for endometrial cancer subtyping from histopathology
npj Precision Oncology · 2026
- Intrinsic tumor factors and extrinsic environmental and social exposures contribute to endometrial cancer recurrence patterns
Research Square · 2026
- Identifying ovarian cancer with AI analysis of abdominal CT scans
Gynecologic Oncology · 2026
- Transforming Gynecologic Cancer Care Through Artificial Intelligence
Clinical Obstetrics & Gynecology · 2025
- Identification of Ovarian High-Grade Serous Carcinoma with Mitochondrial Gene Variation
International Journal of Molecular Sciences · 2025
- Identifying ovarian cancer with machine learning DNA methylation pattern analysis
Scientific Reports · 2025
- A Natural Language Processing Method Identifies an Association Between Bacterial Communities in the Upper Genital Tract and Ovarian Cancer
International Journal of Molecular Sciences · 2025
- 28 Using AI to predict molecular subtype from histopathology slides in endometrial cancer
Journal of Clinical and Translational Science · 2025
- Identifying Ovarian Cancer with Machine Learning DNA Methylation Pattern Analysis
Research Square · 2025
- Improved overall survival with combined chemotherapy and radiation in stage I uterine carcinosarcoma: A National Cancer Database study
Gynecologic Oncology · 2025
- Multimodal deep learning models to predict endometrial cancer recurrence risk by integrating histopathology and genomic data
Gynecologic Oncology · 2025
- Prediction of endometrial cancer recurrence using deep learning analysis of histopathology slides
Gynecologic Oncology · 2025
- Multimodal models for predicting chemotherapy response in high-grade serous ovarian carcinoma: Integration of deep learning models of imaging and genomic data
Gynecologic Oncology · 2025
- Real-World Benchmarking and Validation of Foundation Model Transformers for Endometrial Cancer Subtyping from Histopathology
Research Square · 2025
- ISG15 mediates the function of extracellular vesicles in promoting ovarian cancer progression and metastasis
Journal of Extracellular Biology · 2024
- Gynecologic Oncology×24
- Gynecologic Oncology Reports×5
- International Journal of Gynecological Cancer×3
- Research Square×3
- Scientific Reports×2
- Corinne Calo
Medicine · The Ohio State University
- David E. Cohn
Medicine · The Ohio State University
- Casey Cosgrove
Medicine · The Ohio State University
- Adrian A. Suarez
Medicine · The Ohio State University
- Floor Backes
Medicine · The Ohio State University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 19, 2026.
Claim or correct this profile