Deciphering the morphological features underlying breast cancer behaviour using computational pathology and Artificial intelligence (with focus on the role of the tumour microenvironment)

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Deciphering the morphological features underlying breast cancer behaviour using computational pathology and Artificial intelligence (with focus on the role of the tumour microenvironment)

Background: Breast cancer (BC) is a heterogeneous disease with variable presentations, morphologies, and behaviours. The tumour microenvironment (TME) plays a key role in tumour progression. Molecular and phenotypic alterations in the neoplastic cells and their behaviour usually attracts more atte...

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Bibliographic Details
Main Author:	Ghannam, Suzan
Format:	Thesis (University of Nottingham only)
Language:	English
Published:	2025
Subjects:	Breast cancer; Digital pathology; Biomarkers; Tumour microenvironment; Tumour behaviour; Tumour morphological features
Online Access:	https://eprints.nottingham.ac.uk/81153/

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