Owkin Webinar : Predicting Breast Cancer Outcomes Using AI
|Predicting Breast Cancer Outcomes Using AI Models and Federated Learning|
Date: Oct 13th
Speaker: Dr. Guillaume Bataillon - Pathologist at Institut Curie
8 am PT, 11 am ET, 17:00 CET
In this Breast Cancer Awareness Month, start-up Owkin hosts a free online webinar on October 13th, 2020: Predicting Breast Cancer Outcomes Using AI Models and Federated Learning. As part of the collaboration between Institut Curie & Owkin, Dr Guillaume Bataillon, pathologist at Institut Curie, will share his expertise on the subject alongside other experts from Gustave Roussy, Centre Léon Bérard and Owkin.
Breast cancer is the most common cancer in women worldwide, with nearly 1.7 million new cases diagnosed each year. Though some breast cancers are now treated efficiently, many patients still face poor prognoses and potential relapse. Recently, an array of peer-reviewed studies has shown how clinical diagnostics for cancer are significantly improved when artificial intelligence (AI) is incorporated into disease predictions and treatment strategies. Breast Cancer Awareness Month presents an opportunity to emphasize how novel technologies like AI and federated learning can assist researchers and clinicians and help them face these challenges.
In this Clinical OMICs webinar, a distinguished panel of breast cancer experts and machine learning researchers will explore how clinicians and data scientists can collaborate to accelerate research through the application of novel computational and federated learning techniques.
Owkin, a French-American startup, was co-founded in 2016 by Thomas Clozel, MD, a clinical research doctor and former assistant professor in clinical hematology, and by Gilles Wainrib, PhD, an academic pioneer in the field of Artificial Intelligence in biology. The company was built on the belief that medical research should be collaborative, inclusive, and privacy-preserving. Today, Owkin is building a global research network — using federated learning — connecting data scientists, clinicians, researchers, and pharma on a research platform that keeps the data secure and preserves privacy.