… and a CNN model was successfully implemented for automated multi-class grading or
classification of oral squamous cell carcinoma. We have performed a comparative assessment …

… 1) to make the automated classification methods easy to use with … first automated method for
the radiological classification of … Ideally, an automated segmentation procedure contained in …

… , squamous cell carcinoma, and small cell carcinoma—which are … In this study, we focused
on automated classification of … [5] proposed an automated classification method for brain …

… for renal cell carcinoma subtype classification using scale … to classify a heterogeneous data
set of renal cell carcinoma biopsy … We circumvent user subjectivity using automated analysis …

… scale invariant features for classification of renal cell carcinoma subtypes. Previous work …
We achieve classification accuracy above 90% for a heterogeneous dataset labeled by an …

… The automated classification correctly graded 76% of the low-grade cancers and 71% of the
… fully automated detection and grading of urothelial cell carcinoma. Urothelial cell carcinoma …

… have reported methods to automate carcinoma detection and classification. The … Classification
of lung cancer subtypes as ADC, SCC, large cell carcinoma, and small cell carcinoma was …

… compare two automated machine learning methods for thyroid gland tumor classification
on two … The first method is a feature-based classification originating from common image …

We developed an automated 2-tiered Fuhrman’s grading system for clear cell renal cell
carcinoma (ccRCC). Whole slide images (WSI) and clinical data were retrieved for 395 The …

… cytological images into adenocarcinoma, squamous cell carcinoma, and small cell
carcinoma, obtaining an approximate accuracy of 71%, which is comparable to that obtained by …