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Advanced Bioscience and Biosystems for Detection and Management of Diabetes

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  • © 2022

Overview

Editors:
  1. Kishor Kumar Sadasivuni

    1. Center for Advanced Materials, Qatar University, Doha, Qatar

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  2. John-John Cabibihan

    1. Department of Mechanical and Industrial Engineering, Qatar University, Doha, Qatar

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  3. Abdulaziz Khalid A M Al-Ali

    1. KINDI Center for Computation Research, Doha, Qatar

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  4. Rayaz A. Malik

    1. Weill Cornell Medical College in Qatar, Doha, Qatar

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  • Discusses the causes and types of diabetes
  • Covers the principle and methodology behind different types of techniques to treat diabetes
  • Highlights the importance of artificial intelligence on the early diagnosis of diabetes

Part of the book series: Springer Series on Bio- and Neurosystems (SSBN, volume 13)

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Table of contents (15 chapters)

  1. Front Matter

    Pages i-viii
    Download chapter PDF

  2. Introduction

    • Kishor Kumar Sadasivuni, Mithra Geetha
    Pages 1-7

  3. Review of Emerging Approaches Utilizing Alternative Physiological Human Body Fluids in Non- or Minimally Invasive Glucose Monitoring

    • Sunghoon Jang, Yu Wang, Andre Jang
    Pages 9-26

  4. Current Status of Non-invasive Diabetes Monitoring

    • Sreedevi Paramparambath, Ishwar Maruti Islampure, T. Sabitakala, Muni Raj Maurya, Hajar Morsy, Swathi Yempally et al.
    Pages 27-53

  5. A New Solution for Non-invasive Glucose Measurement Based on Heart Rate Variability

    • Marjan Gusev
    Pages 55-65

  6. Optic Based Techniques for Monitoring Diabetics

    • Hannaneh Monirinasab, Farzaneh Fathi
    Pages 67-89

  7. SPR Assisted Diabetes Detection

    • Choudhary Arjun Sunilbhai, Md.Sabir Alam, Kishor Kumar Sadasivuni, Jamilur R. Ansari
    Pages 91-131

  8. Infrared and Raman Spectroscopy Assisted Diagnosis of Diabetics

    • Nicole M. Ralbovsky, Igor K. Lednev
    Pages 133-164

  9. Photoacoustic Spectroscopy Mediated Non-invasive Detection of Diabetics

    • Deepak Devadiga, T. N. Ahipa
    Pages 165-180

  10. Electrical Bioimpedance Based Estimation of Diabetics

    • Pedro Bertemes-Filho
    Pages 181-197

  11. Millimeter and Microwave Sensing Techniques for Diagnosis of Diabetes

    • Nithusha Kallingal, M. S. Sajna, Mizaj Shabil Sha, Mithra Geetha, Ishwar Maruti Islampure, Nagendra Prasad Devarapalli et al.
    Pages 199-225

  12. Different Machine Learning Algorithms Involved in Glucose Monitoring to Prevent Diabetes Complications and Enhanced Diabetes Mellitus Management

    • Wai-kit Ming, Zonglin He
    Pages 227-241

  13. The Role of Artificial Intelligence in Diabetes Management

    • Amine Rghioui, Jaime Lloret, Abdelmajid Oumnad
    Pages 243-257

  14. Artificial Intelligence and Machine Learning for Diabetes Decision Support

    • Josep Vehi, Omer Mujahid, Ivan Contreras
    Pages 259-272

  15. Commercial Non-invasive Glucose Sensor Devices for Monitoring Diabetes

    • Manickam Tamilselvi, Pandia Raj, Ravikumar Ramlu Vidule, Srinivas Ankanagari
    Pages 273-292

  16. Future Developments in Invasive and Non-invasive Diabetes Monitoring

    • Frédéric Harb, William S. Azar, Hilda E. Ghadieh, Rachel Njeim, Youssef Tawk, Joseph Costantine et al.
    Pages 293-313
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Keywords

About this book

This book covers the medical condition of diabetic patients, their early symptoms and methods conventionally used for diagnosing and monitoring diabetes. It describes various techniques and technologies used for diabetes detection. The content is built upon moving from regressive technology (invasive) and adapting new-age pain-free technologies (non-invasive), machine learning and artificial intelligence for diabetes monitoring and management. This book details all the popular technologies used in the health care and medical fields for diabetic patients. An entire chapter is dedicated to how the future of this field will be shaping up and the challenges remaining to be conquered. Finally, it shows artificial intelligence and predictions, which can be beneficial for the early detection, dose monitoring and surveillance for patients suffering from diabetes

Editors and Affiliations

  • Center for Advanced Materials, Qatar University, Doha, Qatar

    Kishor Kumar Sadasivuni

  • Department of Mechanical and Industrial Engineering, Qatar University, Doha, Qatar

    John-John Cabibihan

  • KINDI Center for Computation Research, Doha, Qatar

    Abdulaziz Khalid A M Al-Ali

  • Weill Cornell Medical College in Qatar, Doha, Qatar

    Rayaz A. Malik

About the editors

Dr. Kishor Kumar Sadasivuni is a Research Assistant Professor and the group leader of Smart Nano Solutions at Center for Advanced Materials, Qatar University. He received his Ph.D. in Materials Science and Engineering from the University of South Brittany at Lorient, France, in 2012.


John-John Cabibihan (Senior Member, IEEE) received the Ph.D. degree in bioengineering, with a specialization in biorobotics, from Scuola Superiore Sant’Anna, Pisa, Italy, in 2007. From 2008 to 2013, he was an Assistant Professor with the Electrical and Computer Engineering Department, National University of Singapore. He is currently an Associate Professor with the Department of Mechanical and Industrial Engineering, Qatar University.


Abdulaziz Al-Ali received the Ph.D. degree in machine learning from the University of Miami, FL, USA, in 2016. He is currently an Assistant Professor with the Computer Science and Engineering Department,College of Engineering, Qatar University. In addition to developing novel machine learning techniques, his research involves building predictive models for textual, image, and sensor-based data. Dr. Al-Ali’s interest remains to be in the machine learning, artificial intelligence, and data mining fields. He now takes the role of the Director of the KINDI Center for Computing Research in Qatar University.


Rayaz A. Malik, BSc. (Hons), MSc., MB ChB, PhD, FRCP graduated in Medicine from the University of Aberdeen in 1991, obtained his MRCP (London) in 1996, PhD from the University of Manchester in 1997 and was elected to become a fellow of the Royal College of Physicians in 2007. He was appointed as Consultant Physician and Senior Lecturer in 2001 and as Professor of Medicine and Consultant Physician in 2008 in Central Manchester University Teaching Hospitals and the University of Manchester. In 2014, he was appointed as Professor of Medicine at Weill Cornell Medicineand remains an honorary Professor of Medicine at the University of Manchester and visiting Professor of Medicine at Manchester Metropolitan University. He was appointed as the Organizational Official in November 2016 and as the Assistant Dean for Clinical Research at Weill Cornell Medicine-Qatar in February 2019. His research focuses on the pathogenesis, assessment and treatment of diabetic and other peripheral neuropathies and central neurodegenerative disorders.

Bibliographic Information

  • Book Title: Advanced Bioscience and Biosystems for Detection and Management of Diabetes

  • Editors: Kishor Kumar Sadasivuni, John-John Cabibihan, Abdulaziz Khalid A M Al-Ali, Rayaz A. Malik

  • Series Title: Springer Series on Bio- and Neurosystems

  • DOI: https://doi.org/10.1007/978-3-030-99728-1

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022

  • Hardcover ISBN: 978-3-030-99727-4Published: 02 July 2022

  • Softcover ISBN: 978-3-030-99730-4Published: 03 July 2023

  • eBook ISBN: 978-3-030-99728-1Published: 01 July 2022

  • Series ISSN: 2520-8535

  • Series E-ISSN: 2520-8543

  • Edition Number: 1

  • Number of Pages: VIII, 313

  • Number of Illustrations: 2 b/w illustrations, 148 illustrations in colour

  • Topics: Biomedical Engineering and Bioengineering, Machine Learning

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