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Neural Network for Detection of Cancer

Principal Investigator
Name
Przemysław Świderski
Degrees
DI
Institution
Lodz University of Technology
Position Title
Student
Email
About this CDAS Project
Study
PLCO (Learn more about this study)
Project ID
PLCO-348
Initial CDAS Request Approval
Mar 9, 2018
Title
Neural Network for Detection of Cancer
Summary
Project will be based on detection of possible correlations between different features in multiple cancers's datasets. After finding correlations, there will be designed and implemented dedicated neural network to predict different medical variables. Neural network will be build by using Python language and open source packages, such as scikit-learn or pandas. Created API will be able to easily show neural net's predictions to pottential users by using simple webservice. Different datasets are needed to provide multiple prediction possibilities.
Aims

Main aim of the project is to build neural network predicting medical variables, such as mortality, treatment or risk of getting illness. Additional goal of the project is to implement REST API of the tool. Potential users will be able to see predictions of neural net by sending request to webservice. Request will contain input values supplied by user of neural network.

Collaborators

Lodz University of Technology