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CNN_test.py
CNN_test.py
 
 
ConfusionMat_MultiClass.m
ConfusionMat_MultiClass.m
 
 
DeTraC_model.ipynb
DeTraC_model.ipynb
 
 
DeepLearning_Keras.py
DeepLearning_Keras.py
 
 
LICENSE
LICENSE
 
 
LogisticRegressionExample.py
LogisticRegressionExample.py
 
 
Matov_3D_CNN_2019.pdf
Matov_3D_CNN_2019.pdf
 
 
Pca_CXR.m
Pca_CXR.m
 
 
README.md
README.md
 
 
Training_DeTraC.m
Training_DeTraC.m
 
 
Training_original_classes.m
Training_original_classes.m
 
 
XGBoost_Model_test.py
XGBoost_Model_test.py
 
 
cnn.py
cnn.py
 
 
construct_dataset_B.m
construct_dataset_B.m
 
 
createLgraphUsingConnections.m
createLgraphUsingConnections.m
 
 
extract_features.m
extract_features.m
 
 
findLayersToReplace.m
findLayersToReplace.m
 
 
kerasMNISTconvnet.R
kerasMNISTconvnet.R
 
 
mnist_convet.py
mnist_convet.py
 
 
readAndPreprocessImage.m
readAndPreprocessImage.m
 
 
regressionUmiseq.R
regressionUmiseq.R
 
 
testMNISTconvnet.R
testMNISTconvnet.R
 
 
txttojpg.R
txttojpg.R
 
 

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Machine learning and deep learning analyses I have run (the Covid Xray DeTraC is developed by the lab of Mohamed Gaber) and a 3D CNN architecture for real-time segmentation and action recognition I configured in the fall of 2019 (R2Plus1D model, PyTorch)

I tested the DeTraC (ResNet18) Python implementation in 2021 https://github.com/xfsala/DeTraC_COVId19, but currently is only available in Matlab

A Python version is available at present here: https://github.com/asmaa4may/DeTraC_COVId19/tree/master/python_code

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www.researchgate.net/publication/382850918_Analysis_of_Multiple_Myeloma_Drug_Efficacy

Topics

deep-learning image-classification logistic-regression convolutional-neural-networks transfer-learning image-segmentation action-recognition 3d-models real-time-analytics lasso-regression resnet-18 separable-convolution sars-cov-2 covid-2019 dilation-convolution 3d-cnn-architecture stochastic-gradient-boosting-classifier r2plus1d-model-pytorch genome-to-image logistic-lasso-regression

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