09:00 | Frederick Klauschen Germany Welcome words from the Congress President |
09:05 | Norman Zerbe Germany Welcome words from ESDIP |
09:10 | Klaus-Robert Müller Germany Artificial Intelligence in Pathology and beyond |
CHAIRS
Gunter Haroske Germany
Sabine Leh Norway
INVITED SPEAKER
Gunter Haroske Germany
Sabine Leh Norway
INVITED SPEAKER
09:30 | Iris Nagtegaal The Netherlands Datasets and structured reporting: the future of pathology? |
ABSTRACTS
09:55 | Andrea Essenwanger (Germany) et al.
Specifying a Pathology Structured Report with HL7 FHIR |
10:05 | Sabine Leh (Norway) et al.
Kidney Biopsy Codes: a multi-hierarchical terminology for non-neoplastic kidney biopsies |
CHAIRS
Johan Lundin Finland
Yuri Tolkach Germany
INVITED SPEAKER
Johan Lundin Finland
Yuri Tolkach Germany
INVITED SPEAKER
10:45 | Peter Boor Germany Deep learning applications in kidney pathology |
ABSTRACTS
11:15 | Rita Sarkis (Switzerland) et al.
MarrowQuant 2.0: clinical application of a user-friendly digital hematopathology tool for human bone marrow trephine biopsies |
11:25 | Juan A. Retamero (United States) et al.
AI model trained to detect breast cancer metastasis to lymph node shows robust performance for micrometastases and isolated tumor cells. |
11:35 | Justinas Besusparis (Lithuania) et al.
Assessment of glomerular patterns of injury by machine learning methods |
11:45 | Linda Studer (Switzerland) et al.
Budding-T-cell score is a potential predictor for more aggressive treatment in pT1 colorectal cancers |
11:55 | Matteo Botteghi (Italy) et al.
CYTOFastUrine: An Innovative Integrated Solution For Automated Urine Cytology Diagnostics |
12:05 | Jessica Calvo (France) et al.
A Multi-Feature AI Solution for Diagnosis Support in Gastric Biopsies: A Prospective Multi-Site Clinical Study |
CHAIR
Albrecht Stenzinger Germany
INVITED SPEAKER
Albrecht Stenzinger Germany
INVITED SPEAKER
13:45 | Frederick Klauschen Germany AI in cancer research and molecular diagnostics |
ABSTRACTS
14:05 | Maximilian Leitheiser (Germany) et al.
Machine Learning Models Predict the Primary Sites of Head and Neck Squamous Cell Carcinoma Metastases Based on DNA Methylation |
14:15 | John Connelly (United Kingdom) et al.
Using machine learning to infer whole genome duplication from tumour nuclear morphology |
14:25 | Nadine Flinner (Germany) et al.
Bagging ensemble cNN outperforms conventional laboratory staining methods in predicting molecular subtypes of gastric adenocarcinoma |
14:35 | Philipp Keyl (Germany) et al.
Patient-level proteomic network prediction by explainable artificial intelligence |
14:45 | Raquel Romero-Garcia (Spain) et al.
A deep learning approach in the prediction of gene mutations using hematoxylin-eosin images in breast cancer |
PANELISTS
Frederick Klauschen Germany
Peter Hufnagl Germany
Inti Zlobec Switzerland
David Horst Germany
CHAIRS
Filippo Fraggetta Italy
Paul van Diest The Netherlands
INVITED SPEAKERS
Filippo Fraggetta Italy
Paul van Diest The Netherlands
INVITED SPEAKERS
16:00 | Philipp Ströbel Germany Implementation of a fully digital workflow: a critical review after two years |
16:20 | Catarina Eloy Portugal Do the best for your patients - start the digital transformation of your lab! |
ABSTRACTS
16:40 | Chris Gorman (United States) et al.
A standard-based computational image analysis workflow for scalable and interoperable AI model development and deployment |
16:50 | Paola Chiara Rizzo (Italy) et al.
Technical and Diagnostic Issues with Whole Slide Imaging in Validation Studies |
17:00 | Rutger H.J. Fick (France) et al.
An AI-supported solution to improve the digital pathology workflow for optimized breast cancer treatment decision-making |
17:10 | Alessandro Caputo (Italy) et al.
A combined molecular/digital approach to the cervical cancer screening program in Sicily (Italy): a preliminary report |
17:20 | Deniz Bayçelebi (Turkey) et al.
Implementation of Digital Pathology Workflow for Routine Primary Diagnosis in a Large Private Hospital Network |