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Augmented intelligence in healthcarea pragmatic and integrated analysis /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Augmented intelligence in healthcareedited by Sushruta Mishra ... [et al.].
Reminder of title:	a pragmatic and integrated analysis /
other author:	Mishra, Sushruta.
Published:	Singapore :Springer Nature Singapore :2022.
Description:	xv, 502 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Artificial intelligenceMedical applications.
Online resource:	https://doi.org/10.1007/978-981-19-1076-0
ISBN:	9789811910760$q(electronic bk.)

Augmented intelligence in healthcarea pragmatic and integrated analysis /
Augmented intelligence in healthcarea pragmatic and integrated analysis /[electronic resource] :edited by Sushruta Mishra ... [et al.]. - Singapore :Springer Nature Singapore :2022. - xv, 502 p. :ill., digital ;24 cm. - Studies in computational intelligence,v. 10241860-9503 ;. - Studies in computational intelligence ;v. 216..

Chapter 1. A bibliometric analysis on the role of artificial intelligence in healthcare -- Chapter 2. Supervised Intelligent Clinical Approach for Breast Cancer Tumour Categorisation -- Chapter 3. Health Monitoring and Integrated Wearables -- Chapter 4. A Comprehensive Review Analysis of Alzheimer Disorder using Machine Learning Approach -- Chapter 5. Machine Learning Techniques in Medical Image: A Short Review -- Chapter 6. Analysis of Diabetic Retinopathy Detection Techniques using CNN Models -- Chapter 7. Experimental Evaluation Of Brain Tumor Image Segmentation and Detection Using CNN Model -- Chapter 8. Effective Deep Learning Algorithms for Personalized Healthcare Services -- Chapter 9. Automatic lung carcinoma identification and classification in CT images using CNN deep learning model -- Chapter 10. Augmented Intelligence: Deep Learning Models for Healthcare -- Chapter 11. Sentiment analysis and emotion detection with healthcare perspective -- Chapter 12. Augmented Intelligence in Mental healthcare: Sentiment analysis & emotion detection with healthcare perspective -- Chapter 13. NLP applications for big data analytics within healthcare -- Chapter 14. Cognitive Computing Driven Healthcare: A Precise Study -- Chapter 15. Cognitive Techniques for Brain Disorder Management: A Future Trend -- Chapter 16. Relevance of Blockchain in Revolutionizing Health Records -- Chapter 17. A Systematic Review on Blockchain Technology: Concepts, Applications, and Prospects in Healthcare -- Chapter 18. Integrated Machine Learning Models for Enhanced Security of Healthcare data -- Chapter 19. Symptoms based Biometric Pattern Detection and Recognition -- Chapter 20. Time Series Analysis of COVID 19 waves in India for Social Good -- Chapter 21. Detection of COVID-19 using A Multi-Scale Deep Learning Network:Covid-MSNet -- Chapter 22. Immersive Technologies in the Healthcare Space -- Chapter 23. Artificial Intelligence in Telemedicine: A Brief Survey -- Chapter 24. Infectious Diseases Reporting System Using Naive Bayes Classification Algorithm -- Chapter 25. A Comprehensive Study of Explainable Artificial Intelligence In Healthcare.

The book discusses how augmented intelligence can increase the efficiency and speed of diagnosis in healthcare organizations. The concept of augmented intelligence can reflect the enhanced capabilities of human decision-making in clinical settings when augmented with computation systems and methods. It includes real-life case studies highlighting impact of augmented intelligence in health care. The book offers a guided tour of computational intelligence algorithms, architecture design, and applications of learning in healthcare challenges. It presents a variety of techniques designed to represent, enhance, and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It also presents specific applications of augmented intelligence in health care, and architectural models and frameworks-based augmented solutions.

ISBN: 9789811910760$q(electronic bk.)

Standard No.: 10.1007/978-981-19-1076-0doiSubjects--Topical Terms:

237917
Artificial intelligence
--Medical applications.

LC Class. No.: R859.7.A78 / A84 2022

Dewey Class. No.: 610.28563

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505 0 $a Chapter 1. A bibliometric analysis on the role of artificial intelligence in healthcare -- Chapter 2. Supervised Intelligent Clinical Approach for Breast Cancer Tumour Categorisation -- Chapter 3. Health Monitoring and Integrated Wearables -- Chapter 4. A Comprehensive Review Analysis of Alzheimer Disorder using Machine Learning Approach -- Chapter 5. Machine Learning Techniques in Medical Image: A Short Review -- Chapter 6. Analysis of Diabetic Retinopathy Detection Techniques using CNN Models -- Chapter 7. Experimental Evaluation Of Brain Tumor Image Segmentation and Detection Using CNN Model -- Chapter 8. Effective Deep Learning Algorithms for Personalized Healthcare Services -- Chapter 9. Automatic lung carcinoma identification and classification in CT images using CNN deep learning model -- Chapter 10. Augmented Intelligence: Deep Learning Models for Healthcare -- Chapter 11. Sentiment analysis and emotion detection with healthcare perspective -- Chapter 12. Augmented Intelligence in Mental healthcare: Sentiment analysis & emotion detection with healthcare perspective -- Chapter 13. NLP applications for big data analytics within healthcare -- Chapter 14. Cognitive Computing Driven Healthcare: A Precise Study -- Chapter 15. Cognitive Techniques for Brain Disorder Management: A Future Trend -- Chapter 16. Relevance of Blockchain in Revolutionizing Health Records -- Chapter 17. A Systematic Review on Blockchain Technology: Concepts, Applications, and Prospects in Healthcare -- Chapter 18. Integrated Machine Learning Models for Enhanced Security of Healthcare data -- Chapter 19. Symptoms based Biometric Pattern Detection and Recognition -- Chapter 20. Time Series Analysis of COVID 19 waves in India for Social Good -- Chapter 21. Detection of COVID-19 using A Multi-Scale Deep Learning Network:Covid-MSNet -- Chapter 22. Immersive Technologies in the Healthcare Space -- Chapter 23. Artificial Intelligence in Telemedicine: A Brief Survey -- Chapter 24. Infectious Diseases Reporting System Using Naive Bayes Classification Algorithm -- Chapter 25. A Comprehensive Study of Explainable Artificial Intelligence In Healthcare.
520 $a The book discusses how augmented intelligence can increase the efficiency and speed of diagnosis in healthcare organizations. The concept of augmented intelligence can reflect the enhanced capabilities of human decision-making in clinical settings when augmented with computation systems and methods. It includes real-life case studies highlighting impact of augmented intelligence in health care. The book offers a guided tour of computational intelligence algorithms, architecture design, and applications of learning in healthcare challenges. It presents a variety of techniques designed to represent, enhance, and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It also presents specific applications of augmented intelligence in health care, and architectural models and frameworks-based augmented solutions.
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