Publication Details
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.