AI Model Development for Digital Pathology

This workshop aims to provide participants with hands-on experience in developing AI models for digital pathology. It focuses on leveraging machine learning and deep learning techniques to analyze histopathological images, identify disease patterns, and assist in accurate diagnostics, ultimately enhancing clinical decision-making

• Understand digital pathology workflows and challenges.
• Learn image preprocessing, annotation, and feature extraction techniques.
• Develop machine learning and deep learning models for histopathological analysis.
• Evaluate and validate AI models for clinical relevance and accuracy.
• Apply AI models to real-world pathology datasets and case studies.

• Undergraduate/postgraduate degree in Pathology, Biotechnology, Bioinformatics, Medical Imaging, Computational Biology, or related fields.
• Professionals in healthcare, diagnostics, hospitals, or pharmaceutical sectors.
• Data scientists and AI/ML engineers interested in medical imaging and pathology applications.
• Individuals with an interest in AI-assisted clinical diagnostics and healthcare innovation.

• Ability to develop AI models for pathology image analysis.
• Knowledge of preprocessing and annotating digital pathology slides.
• Skills in training, testing, and validating AI models for clinical application.
• Understanding the integration of AI models in pathology workflows.
• Insights into AI-driven precision diagnostics and personalized patient care.