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alzheimers_case_study

Detecting Early Alzheimers using MRI data and Machine learning

andysbrainbook

This repository contains the files that generate Andy's Brain Book on ReadTheDocs.

beginning-anomaly-detection-using-python-based-dl

Source Code for 'Beginning Anomaly Detection Using Python-Based Deep Learning' by Sridhar Alla and Suman Kalyan Adari

brain-health-challenge

Project "Understanding Brain Health, EDA & DL with the ADNI Dataset." Convolutional Neural Networks to classify ADNI patients using their MRI Brain Scan.

brain-image-analysis

Paper list and resources on machine learning for brain image (e. g. fMRI and sMRI) analysis.

brainnetworks

Graph Convolutional Neural Networks for Alzheimer’s Classification with transfer learning and HPC methods

calculate-precision-recall-f1score-roc-auc

Precision, recall, f1-score, AUC, loss, accuracy and ROC curve are often used in binary image recognition evaluation issue. The repository calculates the metrics based on the data of one epoch rather than one batch, which means the criteria is more reliable. The program implements the calculation at the end of the training process and every epoch process through two versions independently on keras.

classification-metrics-python

This is a simple python example to recreate classification metrics like F1 Score, Accuracy

classification_report_precision_recall_f1-score_blog_post

computational-neuroscience

Using computational tools to explore the networks underlying cognitive neuroscience

convautoencoderapplications

Experiments on convolutional auto encoder applications (image denoising, removing certain patterns from image etc). The convolutional neural network is build using Keras (tensorflow backend).

dementia-classification-compare-classifiers

Classification of Alzheimer disease using different machine learning models.

diagnosing-adhd-with-convlstm

Classifying ADHD fMRI data with a CNN+LSTM Model

fmri-handbook-2e-code

Code for 2nd edition of fMRI analysis handbook

fmri_data_analysis

kaggle-titanic-challenge

My Solution to Kaggle's Titanic Machine Learning Challenge

keras-image-data-augmentation

keras ImageDataGenerator example folked from justinhoCHN

keras-python-deep-learning-neural-network-api

Preprocess data for training with Keras,Create an artificial neural network with Keras,Train an artificial neural network with Keras,Build a validation set with Keras,Make predictions with an artificial neural network using Keras,Create confusion matrix for predictions from Keras model,Save and load a Keras model,Image preparation for CNN Image Classifier with Keras,Create and train a CNN Image Classifier with Keras,Make predictions with a Keras CNN Image Classifier,Fine-tune VGG16 Image Classifier with Keras ,Data augmentation with Keras,Mapping Keras labels to image classes,Reproducible results with Keras,Initializing and Accessing Bias with Keras,Deploy Keras Neural Network to Flask web service

metrics_evaluation_on_classification_models

Implemented different evaluation metrics like Precision, Recall, f1 score, f beta and receiver operator classification, how they work and can be implemented using numpy.

op1-prediction-of-the-different-progressive-levels-of-alzheimer-s-disease

This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD).

open-neuroscience

skincancerclassification

Skin Cancer Image Classification 75.5% F1 Score