Early detection of infectious bovine keratoconjunctivitis with artificial intelligence.

Vet Res. December 2023;54(1):122.

Shekhar Gupta¹, Larry A Kuehn², Michael L Clawson³

¹ MyAnIML, Overland Park, KS, 66223, USA. shekhar@myaniml.com.; ² United States Department of Agriculture (USDA), Agricultural Research Service (ARS), U. S. Meat Animal Research Center, Clay Center, NE, 68933, USA.; ³ United States Department of Agriculture (USDA), Agricultural Research Service (ARS), U. S. Meat Animal Research Center, Clay Center, NE, 68933, USA. mike.clawson@usda.gov.

Abstract

Artificial intelligence (AI) was developed to distinguish cattle by their muzzle patterns and identify early cases of disease, including infectious bovine keratoconjunctivitis (IBK). It was tested on 870 cattle in four locations, with 170 developing IBK. The AI identified 169 of the 170 cases prior to their identification by veterinarians, and another 17 cases that remained free of IBK signs (sensitivity = 99.4%, specificity = 97.6%). These results indicate the AI can detect emerging IBK cases by muzzle images very early in the disease process and be used as an intervention tool in the prevention of IBK outbreaks.

Keywords

Artificial intelligence; animal welfare; biosecurity; cattle; cattle disease; deep learning; infectious bovine keratoconjunctivitis; muzzles; neural networks; pinkeye;

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