This is a project I've completed as part of the ASSURE US Summer Research Experience of 2022. This is a deep learning model where I've built a machine learning model that classifies whether or not certain brain MRI images have tumors. This model is a convolutional neural network that uses binary classification which outputs 'Yes' if an MRI image has a tumor and 'No' if the image does not have a tumor. For this model, I've first done a train/test split by feeding it images from the Br35H Dataset. I've then further experimented with my model by feeding it images fromthe Brain Image Clean dataset for it to classify more MRI images after it's training/testing phase from Br35H. Learn more from my notebook.
- Matplotlib
- Seaborn
- Br35H :: Brain Tumor Detection 2020 (Data for Model Training)
- Brain Image Clean (Data for Predictions)
- https://www.kaggle.com/code/salikhussaini49/brain-tumor-prediction-97
- https://www.kaggle.com/code/ahmedhamada0/brain-tumor-detection-br35h
- https://www.kaggle.com/code/dinakhalid/brain-tumor-detection
- https://www.youtube.com/watch?v=wQ8BIBpya2k&list=PLQVvvaa0QuDfhTox0AjmQ6tvTgMBZBEXN
- https://auth.udacity.com/sign-up?next=https%3A%2F%2Flearn.udacity.com%2Fcourses%2Fud187
- https://towardsdatascience.com/a-comprehensive-guide-to-convolutional-neural-networks-the-eli5-way-3bd2b1164a53
- https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/learn/lecture/5760236#overview
- https://www.youtube.com/watch?v=2osIZ-dSPGE&t=298s
https://docs.google.com/presentation/d/1lH_k1xCR-QkouAugpUJ8YCih6BRfvfTzXe1CSUXigS8/edit?usp=sharing