[Neural network: A future in pathology?]
Fiche publication
Date publication
avril 2019
Journal
Annales de pathologie
Auteurs
Membres identifiés du Cancéropôle Est :
Dr DEVALLAND Christine, Pr ZERHOUNI Noureddine
Tous les auteurs :
Zemouri R, Devalland C, Valmary-Degano S, Zerhouni N
Lien Pubmed
Résumé
Artificial Intelligence, in particular deep neural networks are the most used machine learning technics in the biomedical field. Artificial neural networks are inspired by the biological neurons; they are interconnected and follow mathematical models. Two phases are required: a learning and a using phase. The two main applications are classification and regression Computer tools such as GPU computational accelerators or some development tools such as MATLAB libraries are used. Their application field is vast and allows the management of big data in genomics and molecular biology as well as the automated analysis of histological slides. The Whole Slide Image scanner can acquire and store slides in the form of digital images. This scanning associated with deep learning algorithms allows automatic recognition of lesions through the automatic recognition of regions of interest previously validated by the pathologist. These computer aided diagnosis techniques are tested in particular in mammary pathology and dermatopathology. They will allow an efficient and a more comprehensive vision, and will provide diagnosis assistance in pathology by correlating several biomedical data such as clinical, radiological and molecular biology data.
Mots clés
Artificial network, Artificial neural networks, Computer-assisted diagnosis, Diagnostic assisté par ordinateur, Digital pathology, Intelligence artificielle, Pathologie numérique, Réseaux de neurones artificiels
Référence
Ann Pathol. 2019 Apr;39(2):119-129