Document detail
ID

oai:HAL:hal-03342265v1

Topic
Veterinarian Autopsy Bayesian Network Decision-support Tool Cattle Diseases [SDV]Life Sciences [q-bio] [INFO.INFO-AI]Computer Science [cs...
Author
Sicard, Vianney Assié, Sébastien Dorso, Laetitia Chocteau, Florian Picault, Sébastien
Langue
en
Editor

HAL CCSD;SCITEPRESS - Science and Technology Publications

Category

technologies: computer sciences

Year

2021

listing date

12/6/2023

Keywords
necropsy process tool diagnosis veterinary ivan support
Metrics

Abstract

International audience; Veterinary autopsy requires a high level of expertise and skills that not all veterinarians necessarily master, especially in the context of the desertification of rural areas.

The development of support systems is a challenging issue, since such a tool, to be considered relevant and accepted by practitioners in their diagnosis process, must avoid any black box effect.

The diagnosis support system we introduce here, IVAN (“Innovative Veterinary Assisted Necropsy”), aims to engage the user in an explicit, understandable, validable and reviewable process, able to cope with the specific issues of cattle necropsy.

Besides, it provides uncertainty management to deal with approximate lesion descriptions.

IVAN relies on a Bayesian network to infer relevant proposals at each step of the diagnostic process.

IVAN was trained on a set of real autopsy cases from autopsy reports, and its performance was assessed using another set of reports.

In addition, the tool had to provide results in short r esponse time and be able to run the application on mobile device and web server.

In addition to demonstrating the feasibility of the approach, IVAN is a first step towards other support systems in other species and in broader contexts than autopsy.

Sicard, Vianney,Assié, Sébastien,Dorso, Laetitia,Chocteau, Florian,Picault, Sébastien, 2021, A Diagnosis Support System for Veterinary Necropsy based on Bayesian Networks, HAL CCSD;SCITEPRESS - Science and Technology Publications

Document

Open

Share

Source

Articles recommended by ES/IODE AI

Predicting risk of cardiovascular disease using retinal OCT imaging
imaging retinal events science computer disease cardiovascular using risk cvd oct