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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
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