1D CNN, is a powerful choice as a technique for the medical image understanding. In our project, we want to apply the CNN into the detection of 4 different TNBC subtypes and achieve classification between the cancerous subtypes. 

The model has the strength of combining preprocessing, feature extraction from the input signal , and classification in a single architecture. It can discern between different cancer subtypes by applying the model to the Raman spectroscopy data to develop the algorithm that can take metabolic data from the patients and classify the cancer subtypes based on the training and fitting results.