Screening for Chagas disease from the electrocardiogram using a deep neural network.

ABSTRACT:

Background

Worldwide, it is estimated that over 6 million people are infected with Chagas disease (ChD). It is a neglected disease that can lead to severe heart conditions in its chronic phase. While early treatment can avoid complications, the early-stage detection rate is low. We explore the use of deep neural networks to detect ChD from electrocardiograms (ECGs) to aid in the early detection of the disease.

Methods

We employ a convolutional neural network model that uses 12-lead ECG data to compute the probability of a ChD diagnosis. Our model is developed using two datasets which jointly comprise over two million entries from Brazilian patients: The SaMi-Trop study focusing on ChD patients, enriched with data from the CODE study from the general population. The model's p

SUBMITTER: Jidling C 

PROVIDER: S-EPMC10361500 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature