Approximate Entropy and Densely Connected Neural Network in the Early Diagnostic of Patients with Chagas Disease

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

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


It is estimated that in the world there are between 6 and 8 million people infected with Chagas disease, mainly in endemic areas of 21 Latin American countries, and in recent years it is slowly becoming a health problem in more urban areas and countries. In that sense, developing diagnosis methods is primordial. That is why this work used a deep neural network to classify 292 subjects (volunteers and patients) composed of 83 health volunteers (Control group); 102 asymptomatic chagasic patients (CH1 group) and 107 seropositive chagasic patients with incipient heart disease (CH2 group). Approximate Entropy ApEn was calculated from the tachograms of the circadian profiles of 24 hours every 5 minutes (288 frames) of each subject, and part of this data were used to train the network. The classification work done by the deep neural network had 98% of accuracy and 98% of precision, validated with the ROC curve, whose AUC values were approximately the unit for each group. Taking into account the good performance, we can consider this deep neural network and approximate entropy as useful tools to have a good early diagnosis about Chagas disease and its cardiac compromise.

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 'Approximate Entropy and Densely Connected Neural Network in the Early Diagnostic of Patients with Chagas Disease'. En conjunto forman una huella única.

Citar esto