PHAROS AI Factory announced the 7th Course of its Training Series, with the title “Quantitative Pathologic Assessment using AI-based Whole-Slide Image Analysis “, under the AI4Health Topic, that successfully took place on March 20th, 2026.
Presentation language: Greek
Audience: This course was intended for pathologists and histopathology professionals, computational biologists and data scientists, oncology researchers and clinicians, medical imaging specialists and pharmaceutical/biotech R&D professionals.
Description: This course introduced AI-driven approaches for quantitative analysis in digital pathology, focusing on automated tissue segmentation, cell classification and feature extraction from whole-slide images (WSIs). Participants explored how deep learning models can analyze histopathology and multiplex immunohistochemistry images to characterize the tumor microenvironment and support clinically relevant predictions, such as mutation status, patient outcomes and treatment response. The session also highlighted key considerations for model validation, infrastructure design and clinical integration of AI tools in modern pathology workflows.
Learning Objectives
By participating, attendees:
- Understood the principles of AI-based whole-slide image analysis and the infrastructure for digital pathology workflows.
- Described deep learning approaches for automated tissue segmentation and cell classification in histopathology.
- Identified quantitative features extractable from H&E and multiplex immunohistochemistry images to characterize tumor microenvironment.
- Evaluated predictive AI models for mutation inference, survival stratification, and treatment response prediction.
- Recognized key considerations for validating and deploying AI-based pathology tools into clinical practice.
Learning Outcomes:
After completion, participants were able to understand:
- AI infrastructure for whole-slide image analysis
- Tissue segmentation and cell classification AI methods
- Quantitative feature extraction from H&E and mIHC images using AI and image analysis techniques
- How predictive models work for mutations, survival, and pCR prediction
- AI deployment strategies in clinical pathology
The course’s presentation material can be found here.
The course’s recordings can be found here.
