PHAROS AI Factory announces the 7th Course of its Training Series, under the title “Quantitative Pathologic Assessment using AI-based Whole-Slide Image Analysis“, under the specialisation AI4Health, held online via Zoom.
Presentation language: Greek
Audience: This course is intended for pathologists and histopathology professionals, computational biologists and data scientists, oncology researchers and clinicians, medical imaging specialists and pharmaceutical/biotech R&D professionals.
Location: Online via Zoom (you will get the zoom link upon registration)
Description:
This course introduces 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 will explore 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 highlights key considerations for model validation, infrastructure design and clinical integration of AI tools in modern pathology workflows.
Learning Objectives
By participating in this webinar, attendees will:
- Understand the principles of AI-based whole-slide image analysis and the infrastructure for digital pathology workflows.
- Describe deep learning approaches for automated tissue segmentation and cell classification in histopathology.
- Identify quantitative features extractable from H&E and multiplex immunohistochemistry images to characterize tumor microenvironment.
- Evaluate predictive AI models for mutation inference, survival stratification, and treatment response prediction.
- Recognize key considerations for validating and deploying AI-based pathology tools into clinical practice.
Learning Outcomes:
After completing the course, participants will be 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 agenda can be found here.
Register to attend by filling out the form here.
