Prediction of respiratory diseases such as COPD(Chronic obstructive pulmonary disease), URTI(upper respiratory tract infection), Bronchiectasis, Pneumonia, Bronchiolitis with the help of deep neural networks or deep learning. We have constructed a deep neural network model that takes in respiratory sound as input and classifies the condition of its respiratory system. It not only classifies among the above-mentioned disease but also classifies if a person’s respiratory system is healthy or not with higher accuracy and precision.
Good day Victor, i was reproducing this deep neural network with GRU code as i followed your research methodology for classifying respiratory diseases based on audio samples (ICBHI), since you did not provide the code for reshaping the dataset to the required input shape format (which is - None, 1, 40) i am having trouble reshaping the dataset for input as i have tried different ways.
Could you please share that code or provide any guidance on how i can do that ? Thank you very much.
I really liked your project so was giving a try , but stucked here
p = list(data[data['patient_id']==int(soundDir[:3])]['disease'])[0]
Can you please help me know what this line is about ..? What is data here ?