Lecture

Machine Learning-Guided Treatment Discovery

Description

This lecture by the instructor focuses on personalized medicine and the omics revolution, where patients receive targeted therapy tailored to their molecular profile. The talk delves into the use of machine learning to predict treatment outcomes and the challenges faced by traditional algorithms. The instructor presents their research on developing robust machine learning models that encode the nature of the problem as a crucial inductive bias. Additionally, the lecture covers topics such as neural optimal transport, conditional neural optimal transport, and evaluating the effectiveness of these models in predicting treatment responses. Future work includes spatiotemporal modeling of tissue structure and interaction to quantify therapy success.

About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.