Artificial Intelligence in Urology : Present and Future / edited by Andrew J. Hung.

Format:

Book

Contributor:

Hung, Andrew J., editor.

Language:

English

Subjects (All):

Artificial intelligence--Medical applications.

Artificial intelligence.

Urology--Technological innovations.

Urology.

Physical Description:

1 online resource (377 pages)

Edition:

First edition.

Place of Publication:

London, England : Academic Press, [2025]

Summary:

This book explores the integration of artificial intelligence (AI) in the field of urology, focusing on its present applications and future potential. Edited by Andrew J. Hung, the text delves into how AI, machine learning, and deep learning technologies are revolutionizing diagnostics and treatment methodologies for various urological conditions, including prostate, kidney, and bladder cancers. The book provides insights into the use of AI in radiomics, pathomics, and genomics, illustrating its role in enhancing clinical workflows, surgical procedures, and personalized medicine. It is intended for healthcare professionals, researchers, and practitioners in urology and computational biomedicine, offering a comprehensive guide to the ethical considerations, technical challenges, and future directions of AI in the medical field. Generated by AI.

Contents:

Front Cover

Artificial Intelligence in Urology

Copyright Page

Dedication

Contents

List of contributors

1 Introduction

2 What is artificial intelligence, machine learning, and deep learning: terminologies explained

2.1 Differences between artificial intelligence/machine learning/deep learning

2.2 Machine learning categories

2.2.1 Supervised machine learning: classification and regression

2.2.2 Unsupervised machine learning

2.2.3 Reinforcement learning

2.3 Deep learning and neural networks

2.3.1 Feedforward neural network

2.3.2 Convolutional neural networks

2.3.3 Recurrent neural networks

2.3.4 Recent advances in deep learning: generative AI and large language models

Artificial intelligence disclosure

References

3 Prostate cancer diagnosis using artificial intelligence methods—radiomics

3.1 Introduction

3.2 Radiomics: fundamentals and concepts

3.3 Prostate imaging modalities

3.3.1 Ultrasound

3.3.2 CT scan

3.3.3 mpMRI

3.3.4 PET scans

3.4 Regulatory considerations

3.5 Integration into clinical workflow Generated by AI.

Notes:

Description based on publisher supplied metadata and other sources.

Description based on print version record.

Part of the metadata in this record was created by AI, based on the text of the resource.

Includes bibliographical references and index.

ISBN:

9780443221316

0443221316