東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Advanced bioscience and biosystems f...

Sadasivuni, Kishor Kumar.

Linked to FindBook

Google Book

Amazon

博客來

Advanced bioscience and biosystems for detection and management of diabetes

Record Type:	Electronic resources : Monograph/item
Title/Author:	Advanced bioscience and biosystems for detection and management of diabetes/ edited by Kishor Kumar Sadasivuni ... [et al.].
other author:	Sadasivuni, Kishor Kumar.
Published:	Cham :Springer International Publishing : : 2022.,
Description:	viii, 313 p. :ill., digital ;24 cm.
[NT 15003449]:	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
Subject:	Diabetes - Diagnosis. -
Online resource:	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
LDR:03098nmm a2200349 a 4500 001 2302004
003 DE-He213
005 20220701103701.0
006 m d
007 cr nn 008maaau
008 230409s2022 sz s 0 eng d
020 $a 9783030997281 $q (electronic bk.)
020 $a 9783030997274 $q (paper)
024 7 $a 10.1007/978-3-030-99728-1 $2 doi
035 $a 978-3-030-99728-1
040 $a GP $c GP
041 0 $a eng
050 4 $a RC660 $b .A38 2022
072 7 $a MQW $2 bicssc
072 7 $a TEC059000 $2 bisacsh
072 7 $a MQW $2 thema
082 0 4 $a 616.462075 $2 23
090 $a RC660 $b .A244 2022
245 0 0 $a Advanced bioscience and biosystems for detection and management of diabetes $h [electronic resource] / $c edited by Kishor Kumar Sadasivuni ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a viii, 313 p. : $b ill., digital ; $c 24 cm.
338 $a online resource $b cr $2 rdacarrier
490 1 $a Springer series on bio- and neurosystems, $x 2520-8543 ; $v v. 13
505 0 $a 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.
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.
650 0 $a Diabetes $x Diagnosis. $3 3601932
650 0 $a Diabetes $x Diagnosis $x Technological innovations. $3 3601933
650 1 4 $a Biomedical Engineering and Bioengineering. $3 3381533
650 2 4 $a Machine Learning. $3 3382522
700 1 $a Sadasivuni, Kishor Kumar. $3 2133894
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Springer series on bio- and neurosystems ; $v v. 13. $3 3601931
856 4 0 $u https://doi.org/10.1007/978-3-030-99728-1
950 $a Engineering (SpringerNature-11647)