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Advanced Bioscience and Biosystems for Detection and Management of Diabetes

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Cover of 'Advanced Bioscience and Biosystems for Detection and Management of Diabetes'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Review of Emerging Approaches Utilizing Alternative Physiological Human Body Fluids in Non- or Minimally Invasive Glucose Monitoring
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    Chapter 3 Current Status of Non-invasive Diabetes Monitoring
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    Chapter 4 A New Solution for Non-invasive Glucose Measurement Based on Heart Rate Variability
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    Chapter 5 Optic Based Techniques for Monitoring Diabetics
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    Chapter 6 SPR Assisted Diabetes Detection
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    Chapter 7 Infrared and Raman Spectroscopy Assisted Diagnosis of Diabetics
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    Chapter 8 Photoacoustic Spectroscopy Mediated Non-invasive Detection of Diabetics
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    Chapter 9 Electrical Bioimpedance Based Estimation of Diabetics
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    Chapter 10 Millimeter and Microwave Sensing Techniques for Diagnosis of Diabetes
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    Chapter 11 Different Machine Learning Algorithms Involved in Glucose Monitoring to Prevent Diabetes Complications and Enhanced Diabetes Mellitus Management
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    Chapter 12 The Role of Artificial Intelligence in Diabetes Management
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    Chapter 13 Artificial Intelligence and Machine Learning for Diabetes Decision Support
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    Chapter 14 Commercial Non-invasive Glucose Sensor Devices for Monitoring Diabetes
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    Chapter 15 Future Developments in Invasive and Non-invasive Diabetes Monitoring
Attention for Chapter 13: Artificial Intelligence and Machine Learning for Diabetes Decision Support
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Chapter title
Artificial Intelligence and Machine Learning for Diabetes Decision Support
Chapter number 13
Book title
Advanced Bioscience and Biosystems for Detection and Management of Diabetes
Published by
Springer, Cham, January 2022
DOI 10.1007/978-3-030-99728-1_13
Book ISBNs
978-3-03-099727-4, 978-3-03-099728-1
Authors

Vehi, Josep, Mujahid, Omer, Contreras, Ivan

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