Prediction of the occurrence of leprosy reactions based on Bayesian networks.

ABSTRACT:

Introduction

Leprosy reactions (LR) are severe episodes of intense activation of the host inflammatory response of uncertain etiology, today the leading cause of permanent nerve damage in leprosy patients. Several genetic and non-genetic risk factors for LR have been described; however, there are limited attempts to combine this information to estimate the risk of a leprosy patient developing LR. Here we present an artificial intelligence (AI)-based system that can assess LR risk using clinical, demographic, and genetic data.

Methods

The study includes four datasets from different regions of Brazil, totalizing 1,450 leprosy patients followed prospectively for at least 2 years to assess the occurrence of LR. Data mining using WEKA software was performed following a two-step p

SUBMITTER: de Andrade Rodrigues RS 

PROVIDER: S-EPMC10411956 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature