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Record Nr. |
UNINA9910564698903321 |
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Titolo |
Augmented Intelligence in Healthcare: A Pragmatic and Integrated Analysis / / edited by Sushruta Mishra, Hrudaya Kumar Tripathy, Pradeep Mallick, Khaled Shaalan |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2022 |
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ISBN |
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Edizione |
[1st ed. 2022.] |
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Descrizione fisica |
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1 online resource (503 pages) |
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Collana |
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Studies in Computational Intelligence, , 1860-9503 ; ; 1024 |
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Disciplina |
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Soggetti |
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Computational intelligence |
Artificial intelligence |
Virtual reality |
Augmented reality |
Big data |
Medical informatics |
Computational Intelligence |
Artificial Intelligence |
Virtual and Augmented Reality |
Big Data |
Health Informatics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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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 |
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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 Mentalhealthcare: 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 Naïve Bayes Classification Algorithm -- Chapter 25. A Comprehensive Study of Explainable Artificial Intelligence In Healthcare. |
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Sommario/riassunto |
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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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