東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Next generation healthcare informatics

Tripathy, B. K.

FindBook

Google Book

Amazon

博客來

Next generation healthcare informatics

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Next generation healthcare informatics/ edited by B. K. Tripathy ... [et al.].
其他作者:	Tripathy, B. K.
出版者:	Singapore :Springer Nature Singapore : : 2022.,
面頁冊數:	xix, 308 p. :ill., digital ;24 cm.
內容註:	Chapter 1. Methods for the recognition of multisource data in intelligent medicine: A review and next generation trends -- Chapter 2. Deep Learning in Healthcare: Challenges and Opportunities -- Chapter 3. Examination of Health Data Performance Depending on the Creative Use of Optimization Methods and Machine Learning Algorithms -- Chapter 4. Effect of computation and cognitive bias in healthcare intelligence and pharmacogenomics -- Chapter 5. Application of Genetic Algorithms in Healthcare: A Review -- Chapter 6. Decision-Making in Healthcare Nano-informatics -- Chapter 7. A Succinct Analytical Study of the Usability of Encryption Methods in Healthcare Data Security -- Chapter 8. IoMT in healthcare industry - Concepts and Applications -- Chapter 9. The Effect of Heuristic Methods Towards Performance of Health Data Analysis -- Chapter 10. AI for Stress Diagnosis at Home Environment -- Chapter 11. Contemporary Technologies to Combat Pandemics and Epidemics -- Chapter 12. Deep Learning for Diabetic Retinopathy Detection: Challenges and Opportunities -- Chapter 13. Deep Reinforcement Based Conversational AI Agent in Healthcare System -- Chapter 14. Deep Learning Empowered Fight against COVID-19: A Survey -- Chapter 15. Application of GAN in Guided Imagery Therapy -- Chapter 16. Digital Transformation in Healthcare Industry: A Survey -- Chapter 17. Application of Deep Learning in Mental Disorder: Challenges and Opportunities.
Contained By:	Springer Nature eBook
標題:	Medical informatics. -
電子資源:	https://doi.org/10.1007/978-981-19-2416-3
ISBN:	9789811924163

Next generation healthcare informatics
Next generation healthcare informatics[electronic resource] /edited by B. K. Tripathy ... [et al.]. - Singapore :Springer Nature Singapore :2022. - xix, 308 p. :ill., digital ;24 cm. - Studies in computational intelligence,v. 10391860-9503 ;. - Studies in computational intelligence ;v. 1039..

Chapter 1. Methods for the recognition of multisource data in intelligent medicine: A review and next generation trends -- Chapter 2. Deep Learning in Healthcare: Challenges and Opportunities -- Chapter 3. Examination of Health Data Performance Depending on the Creative Use of Optimization Methods and Machine Learning Algorithms -- Chapter 4. Effect of computation and cognitive bias in healthcare intelligence and pharmacogenomics -- Chapter 5. Application of Genetic Algorithms in Healthcare: A Review -- Chapter 6. Decision-Making in Healthcare Nano-informatics -- Chapter 7. A Succinct Analytical Study of the Usability of Encryption Methods in Healthcare Data Security -- Chapter 8. IoMT in healthcare industry - Concepts and Applications -- Chapter 9. The Effect of Heuristic Methods Towards Performance of Health Data Analysis -- Chapter 10. AI for Stress Diagnosis at Home Environment -- Chapter 11. Contemporary Technologies to Combat Pandemics and Epidemics -- Chapter 12. Deep Learning for Diabetic Retinopathy Detection: Challenges and Opportunities -- Chapter 13. Deep Reinforcement Based Conversational AI Agent in Healthcare System -- Chapter 14. Deep Learning Empowered Fight against COVID-19: A Survey -- Chapter 15. Application of GAN in Guided Imagery Therapy -- Chapter 16. Digital Transformation in Healthcare Industry: A Survey -- Chapter 17. Application of Deep Learning in Mental Disorder: Challenges and Opportunities.

This edited book provides information on emerging fields of next-generation healthcare informatics with a special emphasis on emerging developments and applications of artificial intelligence, deep learning techniques, computational intelligence methods, Internet of medical things (IoMT), optimization techniques, decision making, nanomedicine, and cloud computing. The book provides a conceptual framework and roadmap for decision-makers for this transformation. The chapters involved in this book cover challenges and opportunities for diabetic retinopathy detection based on deep learning applications, deep learning accelerators in IoT and IoMT, health data analysis, deep reinforcement-based conversational AI agent in healthcare systems, examination of health data performance, multisource data in intelligent medicine, application of genetic algorithms in health care, mental disorder, digital healthcare system with big data analytics, encryption methods in healthcare data security, computation and cognitive bias in healthcare intelligence and pharmacogenomics, guided imagery therapy, cancer detection and prediction techniques, medical image processing for coronavirus, and imbalance learning in health care.

ISBN: 9789811924163

Standard No.: 10.1007/978-981-19-2416-3doiSubjects--Topical Terms:

661258
Medical informatics.

LC Class. No.: R858 / .N48 2022

Dewey Class. No.: 610.285

Next generation healthcare informatics
LDR:03789nmm a2200349 a 4500 001 2302024
003 DE-He213
005 20220607110055.0
006 m d
007 cr nn 008maaau
008 230409s2022 si s 0 eng d
020 $a 9789811924163 $q (electronic bk.)
020 $a 9789811924156 $q (paper)
024 7 $a 10.1007/978-981-19-2416-3 $2 doi
035 $a 978-981-19-2416-3
040 $a GP $c GP
041 0 $a eng
050 4 $a R858 $b .N48 2022
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 610.285 $2 23
090 $a R858 $b .N567 2022
245 0 0 $a Next generation healthcare informatics $h [electronic resource] / $c edited by B. K. Tripathy ... [et al.].
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2022.
300 $a xix, 308 p. : $b ill., digital ; $c 24 cm.
338 $a online resource $b cr $2 rdacarrier
490 1 $a Studies in computational intelligence, $x 1860-9503 ; $v v. 1039
505 0 $a Chapter 1. Methods for the recognition of multisource data in intelligent medicine: A review and next generation trends -- Chapter 2. Deep Learning in Healthcare: Challenges and Opportunities -- Chapter 3. Examination of Health Data Performance Depending on the Creative Use of Optimization Methods and Machine Learning Algorithms -- Chapter 4. Effect of computation and cognitive bias in healthcare intelligence and pharmacogenomics -- Chapter 5. Application of Genetic Algorithms in Healthcare: A Review -- Chapter 6. Decision-Making in Healthcare Nano-informatics -- Chapter 7. A Succinct Analytical Study of the Usability of Encryption Methods in Healthcare Data Security -- Chapter 8. IoMT in healthcare industry - Concepts and Applications -- Chapter 9. The Effect of Heuristic Methods Towards Performance of Health Data Analysis -- Chapter 10. AI for Stress Diagnosis at Home Environment -- Chapter 11. Contemporary Technologies to Combat Pandemics and Epidemics -- Chapter 12. Deep Learning for Diabetic Retinopathy Detection: Challenges and Opportunities -- Chapter 13. Deep Reinforcement Based Conversational AI Agent in Healthcare System -- Chapter 14. Deep Learning Empowered Fight against COVID-19: A Survey -- Chapter 15. Application of GAN in Guided Imagery Therapy -- Chapter 16. Digital Transformation in Healthcare Industry: A Survey -- Chapter 17. Application of Deep Learning in Mental Disorder: Challenges and Opportunities.
520 $a This edited book provides information on emerging fields of next-generation healthcare informatics with a special emphasis on emerging developments and applications of artificial intelligence, deep learning techniques, computational intelligence methods, Internet of medical things (IoMT), optimization techniques, decision making, nanomedicine, and cloud computing. The book provides a conceptual framework and roadmap for decision-makers for this transformation. The chapters involved in this book cover challenges and opportunities for diabetic retinopathy detection based on deep learning applications, deep learning accelerators in IoT and IoMT, health data analysis, deep reinforcement-based conversational AI agent in healthcare systems, examination of health data performance, multisource data in intelligent medicine, application of genetic algorithms in health care, mental disorder, digital healthcare system with big data analytics, encryption methods in healthcare data security, computation and cognitive bias in healthcare intelligence and pharmacogenomics, guided imagery therapy, cancer detection and prediction techniques, medical image processing for coronavirus, and imbalance learning in health care.
650 0 $a Medical informatics. $3 661258
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Health Informatics. $3 892928
650 2 4 $a Machine Learning. $3 3382522
700 1 $a Tripathy, B. K. $3 3601998
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Studies in computational intelligence ; $v v. 1039. $3 3601999
856 4 0 $u https://doi.org/10.1007/978-981-19-2416-3
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)