Free Virtual Summit

BRIDGING THE GAP BETWEEN PATHOLOGY AND COMPUTER SCIENCE

An Independent Digital Pathology Event

     Online

     November 4th, 2022 @ 7:00 AM EST

Free Virtual Summit

Bridging the Gap between Pathology and Computer Science.

An Independent Digital Pathology Event

By providing your email address you are allowing Digital Pathology Place, Inc. and Global Engage Ltd. to send you email messages. Don't worry we will only send you relevant information and if you don't like it you can unsubscribe any time. 

Made Possible By:

Radboud University Medical Center Computational Pathology Group

Radboud university medical center is a leading academic centre for medical science, education, and health care in Nijmegen, The netherlands. The computational pathology group develops, validates and deploys novel medical image analysis methods based on deep learning technology and focusing on computer-aided diagnosis. 

Charles River Laboratories

Charles River provides products and services to help expedite the discovery, early-stage development and safe manufacture of novel drugs and therapeutics. Charles River's Digital Pathology offering supports primary and peer review, telepathology, image analysis, and stereology applications. It is the first non-clinical pathology group in the world with a fully GLP validated digital microscope for completing primary and peer-review pathology evaluations for toxicology studies.

Global Engage Ltd.

Global Engage is on the mission to be the leading interface connecting business and the life sciences; by delivering excellence through the creation of world-class events and content across the globe.

Aleksandra Zuraw, DVM, PhD

Aleksandra is a veterinary pathologist at Charles River Laboratories and a digital pathology publisher at The Digital Pathology Place. Her mission is to bridge the gap between pathology and computer sciente to advance digital pathology as a tool to help more patients and develop better drugs faster. This event is a result of her  sabbtical program at Charles River Laboratories. 

LIVE With Digital Pathology Bridge Builders

November 4th @ 7:00 AM EST

Presented by Aleksandra Zuraw

ONLY LIMITED SEATS AVAILABLE!

Meet the Speakers

JEROEN VAN DER LAAK

Professor of computational Pathology at the Department of Pathology of the Radboud University Medical Center in Nijmegen & guest professor at the Center for Medical Image Science and Visualization (CMIV) in Linkoping, Sweden.

RESEARCH FOCUS:
Improving cancer diagnostics and prognostics with machine learning and large data sets in Pathology

GEERT LITJENS

Assistant Professor at Radboud University Nijmegen Medical Center

RESEARCH FOCUS
Application of modern machine learning methods to oncological pathology (focus on prostate and pancreatic cancer)

FRANCESCO CIOMPI

Assistant Professor of Computational Pathology at Radboud University Medical Center, Nijmegen.

 RESEARCH FOCUS
AI in precision oncology, computer-aided diagnosis for large-scale digital pathology and multi-modal data.

DAAN GEIJS

 PhD candidate in the Computational Pathology Group at Radboud University Nijmegen Medical Center

RESEARCH FOCUS: 
Implementing deep learning in the daily routine of dermatopathologists

LESLIE TESSIER

PhD candidate in the Computational Pathology Group at Radboud University Nijmegen Medical Center  & Resident Physician (Pathology), CHU Angers, France

RESEARCH FOCUS:
Automated assessment of tubule formation in breast cancer

LEANDER VAN EEKELEN

PhD candidate in the Computational Pathology Group at Radboud University Nijmegen Medical Center.

RESEARCH FOCUS:
Improving lung cancer immunotherapy with deep learning

MEYKE HERMSEN

Study manager and PhD candidate in the Computational Pathology Group at Radboud University Nijmegen Medical Center.

RESEARCH FOCUS:
Deep learning applications for renal transplant pathology

KHRYSTYNA FARYNA

PhD candidate in the Computational Pathology Group at Radboud University Nijmegen Medical Center.

RESEARCH FOCUS:
Bridging the clinical integration gap for deep learning-based methods in computational pathology by improving model generalization

EDUARD CHELEBIAN

PhD candidate in the Department of Information Technology at Uppsala University, Sweden.

RESEARCH FOCUS:
 What representations do deep neural networks learn in histopathology imaging and their connection to spatially-resolved gene expression

MILDA POCEVICIUTE

PHD Candidate in the Computer Graphics and Image processing Group at Linköping University, Sweden.

RESEARCH FOCUS:
 Explainable artificial intelligence (XAI), anomaly detection and uncertainty techniques for digital pathology
What You'll Learn On This FREE Event!
LEARN #1:
"What were the beginnings of computational pathology? How far along are we now and where are we heading? What do we need to improve in the current setup to work better and faster?"
LEARN #2:
"Which image analysis approach to choose for your pathology images? Should if be classical computer vision or deep learning based approach? Object detection or semantic segmentation? After this event you will know!"
LEARN #3:
"What other type of data in addition to images can we leverage in computational pathology? How can we integrate them in the research pipeline and what does it mean in clinical pathology?"
Yes, I want to help bridge the gap between PATHOLOGY and COMPUTER SCIENCE. Count me in!
By providing your email address you are allowing Digital Pathology Place, Inc. and Global Engage Ltd. to send you email messages. Don't worry we will only send you relevant information and if you don't like it you can unsubscribe any time. 
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