HM-Detect

HM-Detect is a novel heart murmur detection and classification/characterization method using techniques in sound feature analysis, signal processing, and machine learning.

In this project, several LSTM layers are used to classify the timing of a heart murmur between fundamental sounds S1 and S2 (early-, mid-, late-, or holo-systolic). This method was trained on the CirCor DigiScope Phonocardiogram Database and the Michigan Heart Sound & Murmur Library.

The CirCor Database and Michigan Heart Sound & Murmur Library are available online but are not included in this repository. Extra folders were made to store spectrograms, GAN plots, SSEs, TensorFlowJS models, Time Series Data/Time Series Data Five Seconds plots, and of course the two training databases mentioned before. These folders are referenced multiple times within the code, but are not in the repository as they are very large to upload. The programs required to generate the files in these "extra folders" have been uploaded to this repository.

As of right now, LSTM v9 seems to be the most successful based on ROC curves.

Name		Name	Last commit message	Last commit date
Latest commit History 14 Commits
Class Count.ipynb		Class Count.ipynb
EMD or DMD Test.ipynb		EMD or DMD Test.ipynb
GAN example.ipynb		GAN example.ipynb
Generate MFCC.ipynb		Generate MFCC.ipynb
Generate SSE.ipynb		Generate SSE.ipynb
LSTM v1.ipynb		LSTM v1.ipynb
LSTM v10 (Multi-class Categorical Adam, Filterbanks).ipynb		LSTM v10 (Multi-class Categorical Adam, Filterbanks).ipynb
LSTM v11 (Multi-class Categorical SGD, Filterbanks).ipynb		LSTM v11 (Multi-class Categorical SGD, Filterbanks).ipynb
LSTM v12 (Multi-class Systolic Murmur Timing 4 layers, Filterbanks).ipynb		LSTM v12 (Multi-class Systolic Murmur Timing 4 layers, Filterbanks).ipynb
LSTM v12 AUC ROC Mirco+Marco.png		LSTM v12 AUC ROC Mirco+Marco.png
LSTM v12 AUC ROC Per Class.png		LSTM v12 AUC ROC Per Class.png
LSTM v13 (Multi-class Systolic Murmur Timing 3 layers Filterbanks) - GPU RUN.ipynb		LSTM v13 (Multi-class Systolic Murmur Timing 3 layers Filterbanks) - GPU RUN.ipynb
LSTM v14 (Multi-class Systolic Murmur Timing 1 layer Filterbanks) - GPU RUN.ipynb		LSTM v14 (Multi-class Systolic Murmur Timing 1 layer Filterbanks) - GPU RUN.ipynb
LSTM v2.ipynb		LSTM v2.ipynb
LSTM v3.ipynb		LSTM v3.ipynb
LSTM v4 (Multi-class, filterbanks).ipynb		LSTM v4 (Multi-class, filterbanks).ipynb
LSTM v5 (Multi-class, MFCCs).ipynb		LSTM v5 (Multi-class, MFCCs).ipynb
LSTM v6 (Multi-class Systolic Murmur Timing, Filterbanks).ipynb		LSTM v6 (Multi-class Systolic Murmur Timing, Filterbanks).ipynb
LSTM v6 AUC ROC Micro+Macro.png		LSTM v6 AUC ROC Micro+Macro.png
LSTM v6 AUC ROC Per Class.png		LSTM v6 AUC ROC Per Class.png
LSTM v7 (Multi-class Systolic Murmur Timing, Time Domain).ipynb		LSTM v7 (Multi-class Systolic Murmur Timing, Time Domain).ipynb
LSTM v8 (Multi-Class Systolic Murmur TIming, EMD IMF3).ipynb		LSTM v8 (Multi-Class Systolic Murmur TIming, EMD IMF3).ipynb
LSTM v9 (Multi-class Systolic Murmur Timing 3 layers Filterbanks).ipynb		LSTM v9 (Multi-class Systolic Murmur Timing 3 layers Filterbanks).ipynb
LSTM v9 (With Tensorflow JS Weights Save).ipynb		LSTM v9 (With Tensorflow JS Weights Save).ipynb
LSTM v9 AUC ROC Mirco+Marco.png		LSTM v9 AUC ROC Mirco+Marco.png
LSTM v9 AUC ROC Per Class.png		LSTM v9 AUC ROC Per Class.png
Model Comparisons.xlsx		Model Comparisons.xlsx
Multi-Modal LSTM.pptx		Multi-Modal LSTM.pptx
One-Hot Murmur Timing CSV Creation.ipynb		One-Hot Murmur Timing CSV Creation.ipynb
README.md		README.md
SMOTE + GAN.ipynb		SMOTE + GAN.ipynb
Spectrogram Plots.ipynb		Spectrogram Plots.ipynb
TF GPU Check.ipynb		TF GPU Check.ipynb
TensorFlowJS Model JSON Creation.ipynb		TensorFlowJS Model JSON Creation.ipynb
Time Series Five Seconds Plots.ipynb		Time Series Five Seconds Plots.ipynb
Time Series Plots.ipynb		Time Series Plots.ipynb
[FINAL] Multi Modal LSTM.ipynb		[FINAL] Multi Modal LSTM.ipynb
onehotencoding.csv		onehotencoding.csv
v12weights.h5		v12weights.h5
v13model.h5		v13model.h5
v9model.h5		v9model.h5

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