AI-powered pan-species computational pathology: bridging clinic and wildlife care
K. AbdulJabbar, S. P. Castillo, K. Hughes, H. Davidson, A. M. Boddy, L. M. Abegglen, E. P. Murchinson, T. A. Graham, S. Spiro, C. Palmieri, Y. Yuan
This study develops a pan-species computational pathology atlas using AI to analyze cancer morphology across species, finding that accuracy varies with morphological similarity and introduces a new metric for veterinary applications.
bioRxiv · Mar 5, 2022 · PreprintCancer Biology