B2 Non-refereed book chapter or chapter in a compilation book

Introduction to artificial intelligence techniques for medical image analysis




AuthorsSubasi Abdulhamit

EditorsSubasi Abdulhamit

PublisherElsevier

Publication year2022

Book title Applications of Artificial Intelligence in Medical Imaging

Journal name in sourceApplications of Artificial Intelligence in Medical Imaging

Series titleArtificial Intelligence Applications in Healthcare & Medicine

First page 1

Last page49

ISBN978-0-443-18451-2

eISBN978-0-443-18450-5

DOIhttps://doi.org/10.1016/B978-0-443-18450-5.00010-4

Web address https://www.sciencedirect.com/science/article/abs/pii/B9780443184505000104


Abstract

As the main goal of artificial intelligence (AI) is to provide inference from a sample, it employs statistics theory to develop mathematical models. When a model is constructed, its description and algorithmic solution for understanding must be competent. In some cases, the AI algorithm’s competency may be just as crucial as its classification accuracy. AI is applied in a variety of domains, such as anomaly detection, forecasting, medical signal/image analysis as a decision support component, and so on. The goal of this chapter is to assist scientists in selecting an acceptable AI approach and then guiding them in determining the best strategy by utilizing medical imaging. Furthermore, to introduce readers with the fundamentals of AI before digging into tackling real-world issues with AI methodologies. Machine learning, deep learning, and transfer learning are examples of basic ideas discussed. Topics relating to the various AI methodologies, such as supervised and unsupervised learning, will be covered. As a result, the key AI algorithms are discussed briefly in this chapter. Relevant PYTHON programming codes and routines are provided in each section.



Last updated on 2024-26-11 at 14:24