Team Members: Tobias Stangl - 01530138 Robi Markač - 119337706 Mauro Jurada - 11739653\
To run this program for age classification base on cancer features simply clone/download this reporsitory.
It is required to have python3 installed to run this application. You probably will have to download some libraries to run.
To execute, open command line and navigate to the folder where main.py is located. Run main.py using python3 main.py.
The program will run, classify the data and plot all plots implemented to explain the Classifier and visualize the results.
In our project we will make use of a classification algorithm, extract features, identify feature sets and predict age classes according to these features. Furthermore we will find out what are typical feature levels for specific age‐based tumor disease classes and show the results of our experiments in a technical report.
Today there are a lot of databases available to get data of different cancer types. There have been different researches on cancer using AI for example “DeepGx: Deep Learning Using Gene Expression for Cancer Classification“ which tries to find out different cancer types according to different features. There is still a lot of progress left to be made here.
Obtain, process and format data Select relevant features using feature selection methods (Univariate Selection, Feature Importance, ..) Organize data for training and validation Set up a neural network for classification of age classes Use LIME or LRP for explainable AI and find typical features Visualize the results
Python 3.6+ TensorFlow (Deep learning library for Python) TensorBoard (visualization tool) Expected results Tool processing data, and by self‐learning providing age based tumor disease classes as well as reproducible description.