Advanced bioscience and biosystems for detection and management of diabetes / Kishor Kumar Sadasivuni, John-John Cabibihan, Abdulaziz Khalid A.M. Al-Ali, Rayaz A. Malik, editors.
Sadasivuni, Kishor Kumar, 1986- editor.; Cabibihan, J.-J. (John-John), editor.; Al-Ali, Abdulaziz Khalid A. M., editor.; Malik, Rayaz A., editor.
2022
RC660
Available Online

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Title
Advanced bioscience and biosystems for detection and management of diabetes / Kishor Kumar Sadasivuni, John-John Cabibihan, Abdulaziz Khalid A.M. Al-Ali, Rayaz A. Malik, editors.
ISBN
9783030997281 (electronic bk.)
3030997286 (electronic bk.)
9783030997274
3030997278
DOI
https://doi.org/10.1007/978-3-030-99728-1
Published
Cham : Springer, 2022.
Language
English
Description
1 online resource : illustrations (black and white, and color).
Item Number
10.1007/978-3-030-99728-1 doi
Call Number
RC660
Dewey Decimal Classification
616.4/62075
Summary
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.
Access Note
Access limited to authorized users.
Source of Description
Description based on print version record.
Added Author
Sadasivuni, Kishor Kumar, 1986- editor.
Cabibihan, J.-J. (John-John), editor.
Al-Ali, Abdulaziz Khalid A. M., editor.
Malik, Rayaz A., editor.
Series
Springer series on bio- and neurosystems ; v. 13.
Available in Other Form
Advanced bioscience and biosystems for detection and management of diabetes.
Linked Resources
Online Access
Record Appears in
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Introduction
Review of Emerging Approaches Utilizing Alternative Physiological Human Body Fluids in Non- or Minimally Invasive Glucose Monitoring
Current Status of Non-invasive Diabetics Monitoring
A New Solution for Non-invasive Glucose Measurement Based on Heart Rate Variability
Optics Based Techniques for Monitoring Diabetics
SPR Assisted Diabetics Detection
Infrared and Raman Spectroscopy Assisted Diagnosis of Diabetics
Photoacoustic Spectroscopy Mediated Non-Invasive Detection of Diabetics
Electrical Bioimpedance Based Estimation of Diabetics
Millimeter and Microwave Sensing Technique for Diagnosis of Diabetics
Different Machine Learning Algorithm involved in Glucose Monitoring to Prevent Diabetes Complications and Enhanced Diabetes Mellitus Management
The role of Artificial Intelligence in Diabetes management
Artificial Intelligence and Machine learning for Diabetes Decision Support
Commercial Non-Invasive Glucose Sensor Devices for Monitoring Diabetics
Future Developments in Invasive and Non-Invasive Diabetics Monitoring.

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