Mild-Depression-Detection

Introduction

This project focuses on developing a computer vision model capable of detecting mild depression based on resting state fMRI scans. It explores different machine learning approaches and preprocessing techniques to address this complex challenge.

Project Structure

mild_depression_detection
├── models
│   ├── mobilenet v2
│   ├── svm
│   ├── random forest
│   ├── xgboost
│   └── monai
├── notebooks
│   ├── mobilenet.ipynb
│   ├── model_cross_validation.py
│   ├── model_single_train.py
│   ├── monai.ipynb
│   └── simple_ml_models.ipynb
│   └── simple_ml_models_v2.ipynb
├── scripts
│   ├── descriptors.py
│   ├── preprocessing.py
│   └── scheduler.py
└── .gitignore