Development and internal validation of diagnostic prediction models using machine-learning algorithms in dogs with hypothyroidism.

ABSTRACT:

Introduction

Hypothyroidism can be easily misdiagnosed in dogs, and prediction models can support clinical decision-making, avoiding unnecessary testing and treatment. The aim of this study is to develop and internally validate diagnostic prediction models for hypothyroidism in dogs by applying machine-learning algorithms.

Methods

A single-institutional cross-sectional study was designed searching the electronic database of a Veterinary Teaching Hospital for dogs tested for hypothyroidism. Hypothyroidism was diagnosed based on suggestive clinical signs and thyroid function tests. Dogs were excluded if medical records were incomplete or a definitive diagnosis was lacking. Predictors identified after data processing were dermatological signs, alopecia, lethargy, hematocrit, se

SUBMITTER: Corsini A 

PROVIDER: S-EPMC10758480 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature