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Digital pathology has revolutionized diagnostic workflows by converting histological slides into high-resolution digital images. The integration of AI allows pathologists to analyze large datasets with increased speed, precision, and reproducibility. This workshop covers the fundamentals of AI in pathology, including image preprocessing, feature extraction, and model training for disease detection and classification.
Participants will learn to apply AI algorithms to real-world pathology datasets, develop predictive models, and validate their performance. Emphasis will be placed on practical applications in oncology, hematology, and other clinical specialties, providing insights into improving diagnostic accuracy and enabling personalized patient care.
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
Day 1 – Convolutional Neural Networks
Day 2 – Model Building
Day 3 – Optimization & Transfer Learning
11/28/2025
IST 7:00 PM
11/28/2025 – 11/30/2025
IST 8:00 PM
Prof. Kumud Malhotra, Dean of the University Institute of Physical and Life Sciences with 30 years of experience is an academician and administrator and has attained the highest echelons in the educational sector by managing senior positions, like Director, Dean, Managing Editor, or Editor-in-Chief . . .
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PhD in Computational Mechanics from MIT with 15+ years of experience in Industrial AI. Former Lead Data Scientist at Tesla and current advisor to Fortune 500 manufacturing firms.
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