PhD defence
Artificial Intelligence at the Crossroads of Histopathology: A New Era in Endometrial Cancer Precision Diagnostics and Prognostics
- S.C.M. Fremond - Volinsky
- Date
- Tuesday 1 July 2025
- Time
- Location
-
Academy Building
Rapenburg 73
2311 GJ Leiden
Supervisor(s)
- Prof.dr. V.T.H.B.M. Smit
- Prof. dr. T. Bosse
- dr. N. Horeweg
Summary
Artificial intelligence (AI) is rapidly transforming cancer care, especially since the introduction of digital pathology where tumor slides, previously reviewed by pathologists with a microscope, and now digitized with a scanner. This research explores how it can improve the diagnosis, prognosis, and treatment of endometrial cancer—the most common cancer of the uterus and a growing health concern among women worldwide.
Currently, doctors rely on a combination of microscope analysis, patient data, and molecular tests to estimate the patient’s risk of endometrial cancer coming back and to decide on the best treatment. However, these methods can be costly, slow, and difficult to access in many hospitals. This research investigates whether AI can help solve this problem by analyzing standard pathology slides.
In this thesis, two breakthrough AI models were developed: one that can predict the result of the molecular tests, and another that can estimate the risk of cancer recurrence. Both models use diagnostic pathology images and aim to support faster, more accurate, and more affordable cancer care.
These findings are important because they show that AI can potentially reduce unnecessary treatments, speed up diagnosis, and make personalized care more widely available—especially in settings where advanced molecular tests are not feasible.
PhD dissertations
Approximately one week after the defence, PhD dissertations by Leiden PhD students are available digitally through the Leiden Repository, that offers free access to these PhD dissertations. Please note that in some cases a dissertation may be under embargo temporarily and access to its full-text version will only be granted later.
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General information
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