AI, Pathology & Radiology
Radiology went digital 20 years ago, Pathology is going digital right now. When it comes to AI, what can Pathology learn from the experience of Radiology? We invite you to join a webinar that brings together a pathologist, a radiologist and two technology experts – all work to bring AI to radiology and pathology.
The Good, the Bad and the Biased – How can pathologists assess the correctness of AI?
The ways to assess the correctness of AI solutions and showcase real life examples from Pathology. This is the second webinar in the series “When a Pathologist meet a Mathematician” featuring the pathologist Dr. Aleksandra Zuraw and the mathematician Dr. Chen Sagiv.
AI for Pathologists Course 2020
Session 1: Introduction to Image Analysis and Deep Learning Session 2-4: Neural Networks Training & Architectures Session 5: All about DATA Session 6: Real life examples of Deep Learning in Pathology Session 7: Explainability, Validation and more Session 8: Wet Lab with the DeePathology™ STUDIO
DeePathology STUDIO – Your Personal AI Pathology Platform
Real Life Demonstration of the STUDIO and Automaed Quantification of Tumor Area and Cellilarity in Non-small Cell Lung Cancer (NSCLC) Digital Slides
When a Pathologist meets a Mathematician
On making pathology workflow better
Active Learning for Fast and Efficient Annotation of Medical Images – IMVC 2019
The 10th Israel Machine Vision Conference (IMVC) took place on March 18, 2019 at Pavilion 10, EXPO Tel Aviv. Jacob Gildenblat spoke at a conference on “Active Learning for Fast and Efficient Annotation of Medical Images”.
