Deep Learning and Permutation Entropy in the Stratification of Patients with Chagas Disease

Diego Rodrigo Cornejo, Antonio Ravelo-Garcia, Esteban Alvarez, Maria Fernanda Rodriguez, Luz Alexandra Diaz, Victor Cabrera-Caso, Dante Condori-Merma, Miguel Vizcardo Cornejo

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva


Chagas disease is a life threatening illness that in the last decades was becoming a public health problem because of the change in the epidemiological pattern. It may be silent and asymptomatic in the chronic phase. Hence the necessity of the development of early markers. To achieve this, we propose a deep neural network architecture in order to classify 292 patients into three groups: The Control group with 83 volunteers, the CH1 group with 102 patients with positive serology and no cardiac involvement and the CH2 group with 107 patients with positive serology and incipient heart failure. The used data comes from 24-hour ECG, the RR intervals from each subject was divided in 288 frames of 5 minutes each. Then it was preprocessed using permutation entropy obtaining the circadian profile for each patient. And by applying PCA each patient ended up represented by a vector of 144 entries. This was in turn used for the training of the proposed NN architecture. The classification performed with 91% accuracy and an average of 92% precision, consisting in a great work of classification validated by the AUC in each ROC curve. As this results were obtained with a limited quantity of data, this study can be improved provided with more samples, making this model a tool for analyzing ECG in order to try to do an early evaluation and diagnosis of a cardiac compromise related to the generally silent chronic phase.

Idioma originalInglés
Título de la publicación alojada2022 Computing in Cardiology, CinC 2022
EditorialIEEE Computer Society
ISBN (versión digital)9798350300970
EstadoPublicada - 2022
Evento2022 Computing in Cardiology, CinC 2022 - Tampere, Finlandia
Duración: 4 set. 20227 set. 2022

Serie de la publicación

NombreComputing in Cardiology
ISSN (versión impresa)2325-8861
ISSN (versión digital)2325-887X


Conferencia2022 Computing in Cardiology, CinC 2022

Nota bibliográfica

Publisher Copyright:
© 2022 Creative Commons.


Profundice en los temas de investigación de 'Deep Learning and Permutation Entropy in the Stratification of Patients with Chagas Disease'. En conjunto forman una huella única.

Citar esto