Alkhirsan, Zainab M. Jawad and Abdulhadi, Ali M Hussein and Mohammed, Abrar Abdul Redha and Razzaq, Tabark Hyder and Mohammed, Hussein Shehab and Kazem, Fatima Abdul Ameer (2026) The Role of Artificial Intelligence in Histopathological Image Analysis. Central Asian Journal of Medical and Natural Science, 7 (4). ISSN 2660-4159

Text CAJMNS_The+Role+of+Artificial+Intelligence+in+Histopathological.pdf Download (1MB)

Abstract

Histopathology is the science of diagnosing diseases based on tissue morphology, enabling us to understand what kind of disease (as well as prognosis) a patient has. Artificial intelligence (AI), specifically machine learning and deep learning methods, have reached into the field of pathology to dramatically change. AI analyzes digitized WSIs and identifies complicated morphologic patterns objectively, rapidly, and reliably. Here, we discuss the use of AI in histopathology, with a focus on precision medicine and its role in significant cancer diagnosis such as colorectal, lung and breast cancers. The book also discusses the computational techniques—such as convolutional neural networks (CNNs)—and whole-slide imaging systems behind these advances. AI has the potential to enhance diagnostics accuracy (up to 99%) and speed of slide assessment, while enabling telemedicine in parts without subspecialist expertise, yet a number of challenges remain. Data integrity, algorithmic reliance, cost control, and ethical or legal issues remain major problems. Ultimately, AI is one of the most important breakthroughs in modern pathology with unprecedented levels of precision, speed and personalized medicine.

Item Type:	Article
Uncontrolled Keywords:	Artificial intelligence, Histopathology, Digital pathology, Whole-slide imaging, Deep learning, Convolutional neural networks
Subjects:	H Social Sciences
Depositing User:	admin eprints
Date Deposited:	04 Nov 2026 07:23
Last Modified:	04 Nov 2026 07:23
URI:	http://eprints.umsida.ac.id/id/eprint/17409

Actions (login required)

View Item