Skip to main content
SpringerLink
Log in

Artificial Intelligence and Machine Learning for Healthcare

Vol. 1: Image and Data Analytics

  • Book
  • © 2023

Overview

Editors:
  1. Chee-Peng Lim

    1. Institute for Intelligent Systems Research and Innovation, Deakin University, Waurn Ponds, Australia

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Ashlesha Vaidya

    1. Department of Geriatric and Rehabilitation Medicine, Royal Adelaide Hospital, Adelaide, Australia

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  3. Yen-Wei Chen

    1. College of Information Science and Engineering, Ritsumeikan University, Kusatsu, Japan

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  4. Tejasvi Jain

    1. HCL Technologies Limited, Noida, India

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  5. Lakhmi C. Jain

    1. KES International, Shoreham-by-Sea, UK

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • Presents a sample of recent advances in the theory and applications of artificial intelligence for aging populations
  • Focuses on assisting aging populations using the recently evolved artificial intelligence-based paradigms
  • Is written by experts in the field

Part of the book series: Intelligent Systems Reference Library (ISRL, volume 228)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (11 chapters)

  1. Front Matter

    Pages i-xiii
    Download chapter PDF

  2. An Introduction to Artificial Intelligence in Healthcare

    • Smaranda Belciug
    Pages 1-16

  3. Radiomics: Approach to Precision Medicine

    • Ze Jin, Taiguang Yuan, Yukiko Tokuda, Yasuto Naoi, Noriyuki Tomiyama, Kenji Suzuki
    Pages 17-29

  4. Artificial Intelligence Based Strategies for Data-Driven Radial MRI

    • Giuseppe Placidi, Luigi Cinque, Filippo Mignosi, Matteo Polsinelli, Alessandro Sciarra
    Pages 31-59

  5. Unsupervised Domain Adaptation Approach for Liver Tumor Detection in Multi-phase CT Images

    • Rahul Kumar Jain, Takahiro Sato, Taro Watasue, Tomohiro Nakagawa, Yutaro Iwamoto, Xianhua Han et al.
    Pages 61-78

  6. Multi-stage Synthetic Image Generation for the Semantic Segmentation of Medical Images

    • Paolo Andreini, Simone Bonechi, Giorgio Ciano, Caterina Graziani, Veronica Lachi, Natalia Nikoloulopoulou et al.
    Pages 79-104

  7. Classification of Arrhythmia Signals Using Hybrid Convolutional Neural Network (CNN) Model

    • Evelyn Siao Yung Ern, Dzati Athiar Ramli
    Pages 105-132

  8. Polyp Segmentation with Deep Ensembles and Data Augmentation

    • Loris Nanni, Daniela Cuza, Alessandra Lumini, Andrea Loreggia, Sheryl Brahman
    Pages 133-153

  9. Autistic Verbal Behavior Parameters

    • Daniela López De Luise, Federico Hertzulis, Jesica Peralta, Pablo Pescio, Ben Raúl Saad, Tiago Ibacache
    Pages 155-169

  10. Advances in Modelling Hospital Medical Wards

    • P. Landa, M. Resta, E. Tànfani, A. Testi
    Pages 171-183

  11. Tracking Person-Centred Care Experiences Alongside Other Success Measures in Hearing Rehabilitation

    • Gareth Priday, Sonja Pedell, Jessica Vitkovic, Lauren Story
    Pages 185-210

  12. BioGNN: How Graph Neural Networks Can Solve Biological Problems

    • Pietro Bongini, Niccolò Pancino, Franco Scarselli, Monica Bianchini
    Pages 211-231
Back to top

Keywords

About this book

Artificial intelligence (AI) and machine learning (ML) have transformed many standard and conventional methods in undertaking health and well-being issues of humans.  AL/ML-based systems and tools play a critical role in this digital and big data era to address a variety of medical and healthcare problems, improving treatments and quality of care for patients. 

This edition on AI and ML for healthcare consists of two volumes.  The first presents selected AI and ML studies on medical imaging and healthcare data analytics, while the second unveils emerging methodologies and trends in AI and ML for delivering better medical treatments and healthcare services in the future.

In this first volume, progresses in AI and ML technologies for medical image, video, and signal processing as well as health information and data analytics are presented.  These selected studies offer readers theoretical and practical knowledge and ideas pertaining to recent advances in AI and ML for effective and efficient image and data analytics, leading to state-of-the-art AI and ML technologies for advancing the healthcare sector.

Editors and Affiliations

  • Institute for Intelligent Systems Research and Innovation, Deakin University, Waurn Ponds, Australia

    Chee-Peng Lim

  • Department of Geriatric and Rehabilitation Medicine, Royal Adelaide Hospital, Adelaide, Australia

    Ashlesha Vaidya

  • College of Information Science and Engineering, Ritsumeikan University, Kusatsu, Japan

    Yen-Wei Chen

  • HCL Technologies Limited, Noida, India

    Tejasvi Jain

  • KES International, Shoreham-by-Sea, UK

    Lakhmi C. Jain

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation