An artificial neural network-based model to predict chronic kidney disease in aged cats.

ABSTRACT:

Background

Chronic kidney disease (CKD) frequently causes death in older cats; its early detection is challenging.

Objectives

To build a sensitive and specific model for early prediction of CKD in cats using artificial neural network (ANN) techniques applied to routine health screening data.

Animals

Data from 218 healthy cats ≥7 years of age screened at the Royal Veterinary College (RVC) were used for model building. Performance was tested using data from 3546 cats in the Banfield Pet Hospital records and an additional 60 RCV cats-all initially without a CKD diagnosis.

Methods

Artificial neural network (ANN) modeling used a multilayer feed-forward neural network incorporating a back-propagation algorithm. Clinical variables from single cat visits were selected

SUBMITTER: Biourge V 

PROVIDER: S-EPMC7517863 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature