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Nathan Bollig
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Machine learning for syndromic surveillance using veterinary necropsy reports
N Bollig, L Clarke, E Elsmo, M Craven
PloS one 15 (2), e0228105, 2020
312020
JAK1/2 inhibitors AZD1480 and CYT387 inhibit canine B‐cell lymphoma growth by increasing apoptosis and disrupting cell proliferation
Z Lu, CC Hong, PC Jark, A Assumpção, N Bollig, G Kong, X Pan
Journal of veterinary internal medicine 31 (6), 1804-1815, 2017
222017
Hot topic: Detecting digital dermatitis with computer vision
P Cernek, N Bollig, K Anklam, D Döpfer
Journal of dairy science 103 (10), 9110-9115, 2020
202020
Bayesian and machine learning models for genomic prediction of anterior cruciate ligament rupture in the canine model
LA Baker, M Momen, K Chan, N Bollig, FB Lopes, GJM Rosa, ...
G3: Genes, genomes, genetics 10 (8), 2619-2628, 2020
182020
Comparison of community practitioner and clinical educator expectations of veterinary graduates
A Nichelason, N Bollig, T Bach, M Harris, P Schmidt
Journal of Veterinary Medical Education 50 (5), 582-589, 2023
22023
Detecting digital dermatitis with computer vision.
P Cernek, N Bollig, K Anklam, D Döpfer
12020
Freshwater Mussel Viromes Increase Rapidly in Diversity and Abundance when Hosts Are Released from Captivity into the Wild
JC Richard, TW Lane, RE Agbalog, SL Colletti, TC Leach, CD Dunn, ...
Animals 14 (17), 2531, 2024
2024
Clinical Year Veterinary Students’ Expectations of New Graduate Independence Exceed Their Self-Perceived Competence and Expectations of Community Practitioners
A Nichelason, N Bollig, M Anderson, P Schmidt
Journal of Veterinary Medical Education, e20230041, 2023
2023
A Machine Learning Tutorial for Veterinarians: Examples Using Canine Atopic Dermatitis
N Bollig, D DeBoer, D Döpfer
Transfer learning: leveraging human data to build smarter veterinary AI
N Bollig, A Nichelason
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