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Advanced bioscience and biosystems f...

Sadasivuni, Kishor Kumar.

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Advanced bioscience and biosystems for detection and management of diabetes

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advanced bioscience and biosystems for detection and management of diabetes/ edited by Kishor Kumar Sadasivuni ... [et al.].
其他作者:	Sadasivuni, Kishor Kumar.
出版者:	Cham :Springer International Publishing : : 2022.,
面頁冊數:	viii, 313 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Diabetes - Diagnosis. -
電子資源:	https://doi.org/10.1007/978-3-030-99728-1
ISBN:	9783030997281

Advanced bioscience and biosystems for detection and management of diabetes
Advanced bioscience and biosystems for detection and management of diabetes[electronic resource] /edited by Kishor Kumar Sadasivuni ... [et al.]. - Cham :Springer International Publishing :2022. - viii, 313 p. :ill., digital ;24 cm. - Springer series on bio- and neurosystems,v. 132520-8543 ;. - Springer series on bio- and neurosystems ;v. 13..

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.

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.

ISBN: 9783030997281

Standard No.: 10.1007/978-3-030-99728-1doiSubjects--Topical Terms:

3601932
Diabetes
--Diagnosis.

LC Class. No.: RC660 / .A38 2022

Dewey Class. No.: 616.462075

Advanced bioscience and biosystems for detection and management of diabetes
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520 $a 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.
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