Immunohistochemistry annotations enhance AI identification of lymphocytes and neutrophils in digitized H&E slides from inflammatory bowel disease.

Natalia ZurekYi ZhangDermot P B McGovernAnn E WaltsArkadiusz Gertych

Published in: Computer methods and programs in biomedicine (2024)

to the larger number of immune cells in the NeuLy-IHC dataset (in total 5x more, including 21x more neutrophils) than in the MoNuSAC dataset. Despite being trained on data from inflammatory bowel disease specimens, our model maintained robust performance when tested on previously unseen data derived from cancer specimens. The NeuLy-IHC set provides opportunities for training accurate models to quantify the inflammatory infiltrate in digital histologic slides.

Keyphrases

electronic health record
big data
papillary thyroid
artificial intelligence
oxidative stress
peripheral blood
fine needle aspiration
ulcerative colitis
resistance training
machine learning
data analysis
mass spectrometry
bioinformatics analysis
high intensity