Logo Lanfrica

AI-Powered Tool for Automatically Identifying Environmental Risk Factors of African Swine Fever

Domain:

agriculture

Record type:

software
Creator:
Gubbins, SimonNetDutDip
Editor:
Cen
Publisher:
OSF
Host:avatar
This pilot project presents the methodology for an AI-powered tool with which users can interactively engage with a knowledge base concerning the environmental risk factors for African Swine Fever. Specifically, this project describes a method that uses retrieval-augmented generation and large language models to answer user queries regarding this topic. This provides a valuable resource for researchers, veterinarians, and policymakers, and decreases the burden of manual data extraction.

Tasks

question answering

Tags

African Swine FeverEnvironmentLarge Language ModelsRetrieval-Augmented GenerationSystematic Evidence MapSystematic Review

Licenses

Creative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

Similar

African swine fever virus biotype identification tool

ABSTRACT African swine fever virus biotyping is a recently d

Quantifying risk factors and potential geographic extent of African swine fever across the world

African swine fever (ASF) has spread to many countries in Africa, Europe and Asia in the past decade

Risk Factors for African Swine Fever Transmission in Southeast Asia: A Systematic Review and Meta-Analysis

1. Purpose and Rationale African Swine Fever (ASF) has emerged as the most significant threat to the

Identifying risk factors for Lassa fever infection in Sierra Leone, 2019-2021

Abstract Background Lassa fever (LF) virus

techcode11/AI-Swine-Fever-Detection-System-

This is a Web-based platform that can detect symptoms of African Swine Fever through Image processin

Epidemiology of African Swine Fever Virus