Derya Yakar

UMCG

In short, Derya Yakar's research entails the following:

Artificial Intelligence-based MRI diagnosis of Prostate Cancer: a two-step research approach to realize clinical implementation

This research project is dedicated to developing and implementing a (semi-) autonomous AI system for MRI reporting in the diagnosis of clinically significant prostate cancer (csPCa). The project is aimed at overcoming current challenges such as the shortage of expert prostate radiologists and the increasing demand for MRI scans. The PI-CAI algorithm, originally developed using data from over 12,000 prostate MRI cases, will be elevated to higher levels of automation. This enhancement is expected to significantly improve workflow efficiency and address the capacity challenges in radiology and healthcare.

The project is structured in two primary steps. The first step includes meeting four essential preconditions: ensuring patient acceptance of AI, developing safety control measures, generating prospective pilot data to evaluate safety, diagnostic performance, and workflow efficiency, and preparing for a Randomized Controlled Trial (RCT). The second step involves initiating and conducting the RCT to rigorously test and validate the AI system's effectiveness and practicality in a clinical setting.
Collaborators include co-directors Thomas Kwee (UMCG) and Henkjan Huisman (Radboudumc). Marieke van Gerner-Haan (RUG), Yfke Ongena (RUG), Igle Jan de Jong (UMCG), Thea van Asselt, Dennis Rouw (Martini Hospital), and Maarten de Rooij (Radboudumc).