The system accepts ECG signal files from users. These signals represent the electrical activity of the heart.
Supported formats may include:
WFDB format
ECG waveform data
The uploaded ECG signal is processed to remove noise and normalize the data.
Preprocessing includes:
Signal cleaning
Data normalization
Feature extraction
This step prepares the data for machine learning analysis.
The processed ECG data is passed to a trained deep learning model.
The model identifies abnormal heart patterns that may indicate the presence of Chagas cardiomyopathy.
After analysis, the system generates a prediction.
Possible results include:
Chagas Positive
Chagas Negative
Additional information such as confidence score may also be provided
The system displays the ECG signal and diagnostic result in a clear and understandable format.