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2020  Virtual KOSOMBE Conference:

PAIP2020, AI Pathology Challenge Workshop (Brochure & Extended abstract)

Date: November 12th, 2020
Venue: Virtual, South Korea
Time Table
Presenter
Title
File
14:00-14:15
Jinwook Choi, M.D.
Seoul National University Hospital
Opening Remarks
14:15-15:15
Anant Madabhushi ,
Case Western Reserve University
Keynote speech Ⅰ: AI and Computational Pathology as a Companion 
Diagnostic: Implications for Precision Medicine
15:15-15:25
David Joon Ho,
Memorial Sloan Kettering Cancer Center
Microsatellite Instability Prediction by High-Confident Patches in 
Colorectal Cancer Whole Slide Images
15:25-15:35
Team QuILL,

Sejong University
Random sampling-based deep neural networks for an improved classification of microsatellite instability in colorectal cancer
15:35-15:45
Fan Zhang
Predicting microsatellite instability from histology 
in colorectal cancer by deep learning
15:45-15:55
Team ETRI_DGRC,

Kyungpook National University
Pathological Image Segmentation and Classification with Deep Neural Network
15:55-16:10
Break
16:10-16:30
Kyoungbun Lee,

Seoul National University Hospital
Keynote speech Ⅱ: Clinical Reviews on PAIP2020 Challenge: View of Pathologists
16:30-16:50
Won-Ki Jeong,

Korea University
Keynote speech Ⅲ: PAIP2020 Challenge Technical Reviews
16:50-17:00
Team Sharif HooshPardaz,

Sharif University of Technology
Prediction of Microsatellite Instability in Colorectal Cancer from Whole Slide Images via Deep Neural Networks
17:00-17:10
Team Sen,

Sichuan University
Accurate segmentation tumor areas and prediction microsatellite 
instability in colorectal cancer using a hybrid network
17:10-17:20
Jaewook Lee,

Seoul National University College of Medicine
Transfer Learning with EfficientNet for MSI-H Classification for Colon Adenocarcinoma
17:20-17:30
Team SUTECH,

Shiraz University of Technology
A Deep Learning Approach for Microsatellite Instability 
Prediction in Colorectal Cancer Whole slide Images
17:30-
Award Ceremony and Open Discussion