Year: 2026
Type: book-chapter
Abstract: Medical imaging produces more data than almost any other branch of clinical medicine, and the number of trained eyes available to read it has not kept pace. Artificial intelligence (AI), and deep learning in particular, has moved from research laboratories into reading rooms over the past decade and now assists with tasks that range from sharpening noisy scans to flagging a possible cancer on a screening mammogram. This chapter introduces the subject for students and early-career professionals in radiology and the allied health sciences. It traces how the field grew from rule-based computer-aided detection to modern neural networks, explains the core ideas in plain language, and shows where AI enters the imaging workflow. Landmark clinical studies are summarised alongside the measures used to judge performance. The chapter also examines the practical limits of current tools, including bias, poor generalisation and thin clinical evidence, and outlines the ethical and regulatory questions that accompany their use.
Authors: Dheeraj Kumar, Kartika Sharma, Ankit Shukla
Institution: Chhatrapati Shahu Ji Maharaj University
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: gold
OpenAlex ID: W7223669686