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Use of deep learning to predict chronic wasting disease status based on animal movement.

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Title: Use of deep learning to predict chronic wasting disease status based on animal movement.
Authors: Blaha RL; Department of Wildlife, Fisheries and Aquaculture, Mississippi State University, Mississippi State, MS, 39762, USA., Silva CJ; United States Department of Agriculture, Agriculture Research Service, Western Regional Research Center, Albany, CA, 94710, USA., Cunningham SA; Department of Wildlife, Fisheries and Aquaculture, Mississippi State University, Mississippi State, MS, 39762, USA.; Alexander Center for Applied Population Biology, Lincoln Park Zoo, Chicago, IL, 60614, USA., DeVivo MT; Department of Veterinary Sciences, University of Wyoming, Laramie, WY, 82070, USA.; Washington Department of Fish and Wildlife, Spokane Valley, Washington, USA., Edmunds DR; Department of Veterinary Sciences, University of Wyoming, Laramie, WY, 82070, USA.; Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO, 80523, USA., Boudreau MR; Department of Wildlife, Fisheries and Aquaculture, Mississippi State University, Mississippi State, MS, 39762, USA. mel.r.boudreau@gmail.com.
Source: Movement ecology [Mov Ecol] 2026 Jun 10. Date of Electronic Publication: 2026 Jun 10.
Publication Type: Journal Article
Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 101635009 Publication Model: Print-Electronic Cited Medium: Print ISSN: 2051-3933 (Print) Linking ISSN: 20513933 NLM ISO Abbreviation: Mov Ecol
Database: MEDLINE Ultimate
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PubType: Academic Journal
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  Data: <searchLink fieldCode="AU" term="%22Blaha+RL%22">Blaha RL</searchLink>; Department of Wildlife, Fisheries and Aquaculture, Mississippi State University, Mississippi State, MS, 39762, USA.<br /><searchLink fieldCode="AU" term="%22Silva+CJ%22">Silva CJ</searchLink>; United States Department of Agriculture, Agriculture Research Service, Western Regional Research Center, Albany, CA, 94710, USA.<br /><searchLink fieldCode="AU" term="%22Cunningham+SA%22">Cunningham SA</searchLink>; Department of Wildlife, Fisheries and Aquaculture, Mississippi State University, Mississippi State, MS, 39762, USA.; Alexander Center for Applied Population Biology, Lincoln Park Zoo, Chicago, IL, 60614, USA.<br /><searchLink fieldCode="AU" term="%22DeVivo+MT%22">DeVivo MT</searchLink>; Department of Veterinary Sciences, University of Wyoming, Laramie, WY, 82070, USA.; Washington Department of Fish and Wildlife, Spokane Valley, Washington, USA.<br /><searchLink fieldCode="AU" term="%22Edmunds+DR%22">Edmunds DR</searchLink>; Department of Veterinary Sciences, University of Wyoming, Laramie, WY, 82070, USA.; Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO, 80523, USA.<br /><searchLink fieldCode="AU" term="%22Boudreau+MR%22">Boudreau MR</searchLink>; Department of Wildlife, Fisheries and Aquaculture, Mississippi State University, Mississippi State, MS, 39762, USA. mel.r.boudreau@gmail.com.
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  Data: <searchLink fieldCode="JN" term="%22101635009%22">Movement ecology</searchLink> [Mov Ecol] 2026 Jun 10. <i>Date of Electronic Publication: </i>2026 Jun 10.
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        Value: 10.1186/s40462-026-00668-4
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        Text: English
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      – TitleFull: Use of deep learning to predict chronic wasting disease status based on animal movement.
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            – D: 10
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              Text: 2026 Jun 10
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