HALO Clinical AI

8 September 2021 | Digital pathology provides an advantage of automatizing many routine pathological tasks via computational algorithms and tools. The reporting of prostate cases is time-consuming due to a large number of slides per case. Moreover, tumor aggressivity grading (Gleason score) is well known for its subjective nature and high levels of interobserver variability. In this webinar, we will demonstrate a deep learning-based tool developed for the detection of prostate cancer in histological slides (prostate biopsies and prostatectomy specimens) and its histological grading (Gleason grading). We will present the results of the actual validation study showing high levels of accuracy in both tasks. We will discuss the practical aspects of the implementation of such tools in the diagnostic routine.