… In summary, we developed a novel AI-based histopathological image classification approach
for CRC diagnosis using deep learning, which achieved the best performance with the …

… Recent techniques have been proposed to improve the classification performance of
histopathological image sections. For instance, Nazeri et al. (2018) introduced a two-stage CNN, …

… and machine learning techniques to create an algorithm that could automatically segment
nuclei from histological images. … the tremendous potential of artificial intelligence techniques to …

… This section examines the performance of several classification methods such as RF, KNN,
… and Neural Network. In: Proc. of the 3rd International Conference on artificial intelligence and …

… CAD systems applied to histopathological images. In general, artificial intelligence (AI) has
… types and the best retrieval performance was obtained for prostate images. In [107], the …

… Histopathological image analysis is the gold standard to … The increasing use of artificial
intelligence (AI) in the … to evaluate the application and performance of ML and DL algorithms in …

… Routine histopathology images of tissue specimens stained with hematoxylin and eosin (…
In summary, the performance of DL systems to predict MSI status is very high. This could be one …

… archive of WSIs to verify the performance of an image search engine for digital pathology. …
The BoB indexing enables Yottixel to search a large archive of histopathology images very …

… Stain normalization is important in histopathology images because the inconsistencies
created due to various factors are removed, which boosts the performance of the model. Two …

… In this review we focus on machine learning-based digital histopathology image analysis …
of histopathological analyses that machine learning can operate within: whole slide image (WSI…