Review Article
Author Details :
Volume : 9, Issue : 3, Year : 2024
Article Page : 146-150
https://doi.org/10.18231/j.jdpo.2024.030
Abstract
Computational pathology is a flourishing field at the intersection of pathology, computer science, and artificial intelligence (AI). By leveraging advanced image analysis algorithms, machine learning (ML), and deep learning techniques, computational pathology is poised to revolutionize the diagnostic process in clinical settings. This review article discusses key developments in computational pathology, explores various AI-powered tools used in digital histopathology, and examines the potential benefits and challenges of integrating computational techniques in routine pathology practice.
Keywords: Computational pathology, Artificial intelligence (AI), Machine learning (ML), Deep learning, Convolutional neural networks (CNNs)
How to cite : Kotian T, Computational pathology - Transforming diagnosis through machine learning and AI. IP J Diagn Pathol Oncol 2024;9(3):146-150
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Received : 19-08-2024
Accepted : 13-09-2024
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