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Recommender Systems for Medicine and Music

  • Book
  • © 2021

Overview

Editors:
  1. Zbigniew W. Ras

    1. Department of Computer Science, University of North Carolina at Charlotte, Charlotte, USA

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  2. Alicja Wieczorkowska

    1. Department of Multimedia, Polish-Japanese Academy of Information Technology, Warsaw, Poland

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    You can also search for this editor in PubMed   Google Scholar

  3. Shusaku Tsumoto

    1. Department of Medical Informatics, Faculty of Medicine, Shimane University, Izumo, Japan

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    You can also search for this editor in PubMed   Google Scholar

  • Presents applications of Recommender Systems for Medicine and Music
  • Recent applied research on recommender systems
  • Written by leading experts in the field

Part of the book series: Studies in Computational Intelligence (SCI, volume 946)

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Table of contents (14 chapters)

  1. Front Matter

    Pages i-xvi
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  2. Recommendation Systems in Healthcare

    • Madlen Ivanova, Zbigniew W. Raś
    Pages 1-11

  3. Recommender Systems in Healthcare: A Socio-Technical Systems Approach

    • Mila Kwiatkowska
    Pages 13-28

  4. Computer Methods for Localization of the Subthalamic Nucleus During Deep Brain Stimulation Surgeries for Treatment of Parkinson Disease

    • Konrad A. Ciecierski
    Pages 29-53

  5. Stutter Detection and Remediation in Speech

    • Ayman Hajja, Pierre Arbajian
    Pages 55-74

  6. Personalizing Patients to Enable Shared Decision Making

    • Mamoun T. Mardini, Amal Hashky, Zbigniew W. Raś
    Pages 75-90

  7. An LSTM-based Approach for Insulin and Carbohydrate Recommendations in Type 1 Diabetes Self-Management

    • Jeremy Beauchamp, Razvan Bunescu, Cindy Marling
    Pages 91-106

  8. Music Recommendation Systems: A Survey

    • Mariusz Kleć, Alicja Wieczorkowska
    Pages 107-118

  9. Repeated Listens in the Music Discovery Process

    • Brian Manolovitz, Mitsunori Ogihara
    Pages 119-134

  10. What Songs We Listen to Together: Automatic Music Selection for Groups

    • Jun’ichi Suzuki, Tetsuro Kitahara
    Pages 135-152

  11. Body Data for Music Information Retrieval Tasks

    • Tejaswinee Kelkar
    Pages 153-165

  12. Music Recommendation Based on Emotion Tracking of Musical Performances

    • Jacek Grekow
    Pages 167-186

  13. Music and Healthcare Recommendation Systems

    • Mariusz Kleć, Alicja Wieczorkowska
    Pages 187-195

  14. Emotion-Based Music Recommender System for Tinnitus Patients (EMOTIN)

    • Katarzyna A. Tarnowska
    Pages 197-221

  15. A Model of Typhlo Music Therapy in Educational and Rehabilitation Work with Visually Impaired Persons

    • Pawel Cylulko, Joanna Gladyszewska-Cylulko
    Pages 223-236
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Keywords

About this book

Music recommendation systems are becoming more and more popular. The increasing amount of personal data left by users on social media contributes to more accurate inference of the user’s musical preferences and the same to quality of personalized systems. Health recommendation systems have become indispensable tools in decision making processes in the healthcare sector. Their main objective is to ensure the availability of valuable information at the right time by ensuring information quality, trustworthiness, authentication, and privacy concerns. Medical doctors deal with various kinds of diseases in which the music therapy helps to improve symptoms. Listening to music may improve heart rate, respiratory rate, and blood pressure in people with heart disease. Sound healing therapy uses aspects of music to improve physical and emotional health and well-being. The book presents a variety of approaches useful to create recommendation systems in healthcare, music, and in music therapy.



Editors and Affiliations

  • Department of Computer Science, University of North Carolina at Charlotte, Charlotte, USA

    Zbigniew W. Ras

  • Department of Multimedia, Polish-Japanese Academy of Information Technology, Warsaw, Poland

    Alicja Wieczorkowska

  • Department of Medical Informatics, Faculty of Medicine, Shimane University, Izumo, Japan

    Shusaku Tsumoto

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