Diagnostic Performance of Machine Learning Methods in Breast Microwave Sensing

This repository contains the code used to perform the analysis and create the figures in the publication [1].

1. T. Reimer and S. Pistorius, "The diagnostic performance of machine learning in breast microwave sensing on a large open-access experimental dataset," IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology, submitted.

The open-access dataset described here was used as the dataset in this work. The specific files used here are available here.

Getting Started

Prerequisites

The python requirements are:

• Python >= 3.6
• Libraries in the requirements.txt file:
  • tensorflow
  • keras
  • sklearn
  • statsmodels

Authors

• Tyson Reimer¹
• Dr. Stephen Pistorius^1,2

1. Department of Physics & Astronomy, University of Manitoba, Winnipeg, Manitoba, Canada
2. Research Institute in Oncology and Hematology, University of Manitoba, Winnipeg, Manitoba, Canada

License

This project is licensed under the Apache 2.0 License. See the LICENSE file for more information.