Title: Prediction of HER2 status in breast cancer directly from histopathology images using deep learning.
This repository hosts my MSc project, which is currently being completed.
├── README.md <- The top-level README for developers using this project.
├── data (saved locally)
│ ├── external <- Data from third party sources.
│ ├── interim <- Intermediate data that has been transformed.
│ ├── processed <- The final data for modeling.
│ └── raw <- The original data.
│
├── models <- Trained models, model predictions, or model summaries (saved on server)
│
├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
│ the creator's initials, and a short `-` delimited description, e.g.
│ `1.0-jqp-initial-data-exploration`.
│
├── reports <- Generated analysis.
│ └── data figs <- Figures generated from data exploration
│ └── exploration <- Generated images for exploratory purposes, and to be used in thesis
│ └── results <- Graphics and figures generated from model testing
│
├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`
│
├── src <- Source code for use in this project.
│ ├── __init__.py <- Makes src a Python module
│ │
│ ├── data <- Scripts to generate and pre-process data
│ │ └──
│ │
│ ├── models <- Scripts to initialise, train and test models and then use trained models to make
│ │ │ predictions
│ │ ├── predict_model.py
│ │ └── train_model.py
│ │
Project based on the cookiecutter data science project template. #cookiecutterdatascience