Enhancing AI Accessibility in Veterinary Medicine: Linking Classifiers and Electronic Health Records

TL;DR

This paper introduces Anna, a free software tool that integrates machine learning classifiers with veterinary electronic health records to improve diagnostic accuracy and patient care despite system limitations.

Contribution

The paper presents Anna, a novel, freely-available software that enables real-time ML classifier integration with veterinary EHRs, overcoming existing system rigidity and resource constraints.

Findings

Anna successfully integrates ML classifiers with veterinary EHRs in real-time.

The tool improves diagnostic decision-making in veterinary practice.

Open-source availability promotes wider adoption and further development.

Abstract

In the rapidly evolving landscape of veterinary healthcare, integrating machine learning (ML) clinical decision-making tools with electronic health records (EHRs) promises to improve diagnostic accuracy and patient care. However, the seamless integration of ML classifiers into existing EHRs in veterinary medicine is frequently hindered by the rigidity of EHR systems or the limited availability of IT resources. To address this shortcoming, we present Anna, a freely-available software solution that provides ML classifier results for EHR laboratory data in real-time.