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Optimizing lung cancer treatments from public clinical trial data

Principal Investigator

Name
Shimon Sheiba

Degrees
M.Sc

Institution
Causalis.ai

Position Title
Graduate

Email
shimon@causalis.ai

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-729

Initial CDAS Request Approval
Apr 22, 2021

Title
Optimizing lung cancer treatments from public clinical trial data

Summary
In this research, I intend to perform SOTA causal inference methods powered by interoperable AI models in order to discover and understand what are the optimal treatments for different patient profiles.

Aims

- Get familiar with clinical trial data - depth and size
- Analyze the dependencies in the data
- Explore different machine learning models for personalized medicine.

Collaborators

None