ECP 2023 Final Programme

Tuesday, 12 Sept 56 Scientific Programme a Tuesday 006 09:20–09:30 IDH status prediction in gliomas using H&E slides and deep learning Yuval Friedmann, Israel D. Roitman, N. Shelestovich, I. Barshack, S. Ben Amitay 007 10:30–10:40 A look at scanner introduced variation in contrast, resolution, and colour across 10 different models of whole slide imaging (WSI) scanner Hayley Pye, United Kingdom D. Brettle, D. Kaye, C. Dunn, M. Humphries, D. Treanor 008 10:40–10:50 Towards an open-source Transformer-based multiclass segmentation pipeline for basic kidney histology Pieter Valkema, The Netherlands J. Long, J. Li, S. Florquin, M. Naesens, T. Nguygen, S. Meziyerh, A. de Vries, O. de Boer, F. Verbeek, Z. Xiong, J. Kers 009 10:50–11:00 Computationally-derived stromal pheno- types, along with tumour-infiltrating lymphocytes, are associated with progres- sion-free survival in high-grade serous ovar- ian carcinoma digital pathology slides Cédric Walker, Switzerland L. van Wagensveld, J. Sanders, R. Kruitwagen, M. van der Aa, G. Sonke, K. Van de Vijver, S. Rottenberg, H. Horlings, A. Janowczyk 010 11:00–11:10 Automated diagnostic coding (SNOMED- CT) from narrative pathology reports using natural language processing Giorgio Cazzaniga, Italy V. L’Imperio, F. Pagni 011 11:10–11:20 Resizing and recompression of pathology whole slide images for affordable long term storage Luis Alfaro, Spain M. Roca 012 11:20–11:30 HPV detection in oropharyngeal squamous cell carcinoma: comparison of morphology and artificial intelligence Stephanie Craig, United Kingdom V. Gaborieau, R. Gault, K. McCombe, A. Moyes, Y. Sun, T. Wang, A. Schache, T. Jones, J. Risk, P. Gunning, P. Brennan, J. James, B. Abedi-Ardekani 013 11:30–11:40 Artificial intelligence’s impact on prostatic needle biopsies’ diagnostics Evelin Torresani, Italy L. Cima, M. Gentilini, E. Bragantini, F. Carbone, L. Maccio, M. Disanto, C. Sartori, S. Grassi, L. Morelli, T. Cai, M. Brunelli, C. Doglioni, M. Barbareschi 014 11:40–11:50 OvarIA: a deep learning approach for BRCA somatic mutations detection in high-grade ovarian cancer based on an innovative tumour segmentation method from whole-slide images Raphaël Bourgade, France N. Rabilloud, T. Perennec, T. Pecot, C. Garrec, C. Delnatte, S. Bézieau, A. Lespagnol, M. De Tayrac, S. Henno, C. Sagan, C. Toquet, J. Mosnier, S. Kammerer- Jacquet, D. Loussouarn 015 11:50–12:00 An international multi-institutional valida- tion study of deep learning-based classifier for prostate cancer detection and Gleason grading in biopsy samples Yuri Tolkach, Germany V. Ovtcharov, A. Pryalukhin, M. Eich, N. Gaisa, M. Braun, W. Hulla, G. Netto, P. Caie, R. Büttner