Classifying CWD-Infected Elk Using Recurrent Neural Networks on GPS Movement Data

Overview

Development stage

DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.

High-impact designation

Not high-impactSource: c) Not high-impact

Impact justification

Not reported

Start date

2025-01-01 (day precision)Source: 1/1/2025

Withheld from public reporting

NoSource: a) No

Mission

Topic area

Energy and the Environment

Operational functions

Clinical and medical Derived by keyword rules; see methodology

Problem the AI is intended to solve

Chronic Wasting Disease is difficult and costly to diagnose using traditional biological testing. However, the disease affects an elk's behavior and movement over time. By analyzing GPS tracking data with AI — specifically, Recurrent Neural Networks (RNNs) — the model aims to: Automatically identify movement patterns indicative of CWD infection, Enable earlier or non-invasive detection of disease, and Support wildlife disease surveillance and management decisions

Expected benefits

helps wildlife managers detect CWD in elk early using GPS movement data, reducing the need for costly and invasive testing. It supports faster, data-driven decisions for disease control and wildlife management, protecting both animal health and resources

System outputs

The AI system outputs a classification label for each elk—CWD-infected or not infected—based on patterns in their GPS movement data.

Technology

AI classification

Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…

System name(s)

Not reported

Custom-developed code

No

Public source code

Not reported

Sourcing

How it was built

Developed in-houseSource: b) Developed in-house

Vendor (as reported)

Not reported

Vendors (standardized)

None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII

No

Privacy Impact Assessment

Not reported

Authorization to Operate

No

Demographic features

k) None of the above

Training and evaluation data

The model is trained and evaluated using GPS movement data from collared elk, labeled with confirmed CWD infection status through biological testing.

Federal Data Catalog

Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Potential impacts and how they were identified

Not reported