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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 7: Infrared and Raman Spectroscopy Assisted Diagnosis of Diabetics
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Chapter title
Infrared and Raman Spectroscopy Assisted Diagnosis of Diabetics
Chapter number 7
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_7
Book ISBNs
978-3-03-099727-4, 978-3-03-099728-1
Authors

Ralbovsky, Nicole M., Lednev, Igor K.

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