Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics

1. Auflage 2022
ISBN: 978-0-367-67633-9
Verlag: CRC Press

Buch, Englisch, 240 Seiten, Format (B × H): 161 mm x 240 mm, Gewicht: 531 g

Reihe: Innovations in Big Data and Machine Learning

In the last two decades, machine learning has developed dramatically and is still experiencing a fast and everlasting change in paradigms, methodology, applications and other aspects. This book offers a compendium of current and emerging machine learning paradigms in healthcare informatics and reflects on their diversity and complexity.

Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research. It provides many case studies and a panoramic view of data and machine learning techniques, providing the opportunity for novel insights and discoveries. The book explores the theory and practical applications in healthcare and includes a guided tour of machine learning algorithms, architecture design and interdisciplinary challenges.

This book is useful for research scholars and students involved in critical condition analysis and computation models.

Zielgruppe

Academic, Professional, and Undergraduate Advanced

Autoren/Hrsg.

Kumar, Abhishek

Dubey, Ashutosh Kumar

Anavatti, Sreenatha G.

Rathore, Pramod Singh

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
• Technische Wissenschaften Technik Allgemein Industrial Engineering
• Mathematik | Informatik Mathematik Operations Research
• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik

Inhaltsverzeichnis

1. Machine Learning in Healthcare. 2. Feature Extraction and Applications of Bio Signals. 3. Machine Learning Methods for Managing Parkinson’s Disease. 4. Challenges of Medical Text and Image Processing. 5. Machine Learning Solutions in Computer-Aided Medical Diagnosis. 6. Rule Learning in Healthcare and Health Services Research. 7. Diagnosis in Medical Imaging. 8. Identifying Diseases and Diagnosis Using Machine Learning. 9. Machine Learning-Based Behavioral Modification. 10. Smart Health Records. 11. Treatment Recommendation System. 12. Smart Health Informatics System. 13. Natural Language Processing Utilization in Healthcare. 14. Clinical Decision Support and Predictive Analytics. 15. Bioinformatics and Biometrics. 16. Human Computer Interfaces and Usability. 17. Education and Capacity Building. 18. Learning Analytics for Competence Assessment. 19. Patient Simulators. 20. Serious Gaming. 21. Patient Empowerment and Engagement. 22. Social Media, Mobile Apps, and Patient Portals. 23. Human Factors and Technology Adoption. 24. Surveillance System. 25. Robotics. 26. Object Detection. 27. Traffic Analysis. 28. Big Data in Healthcare Systems. 29. Advanced Decision-Making and Data Analytics. 30. Emergence of Decision Support Systems. 31. Big Data Based Frameworks and Machine Learning. 32. Predictive Analysis and Modeling. 33. Security and Privacy with Machine Learning Systems. 34. Role of Social Media in Healthcare Analytics. 35. Big Data Based Case Studies for Healthcare Analytics. 36. Machine Learning and Deep Learning Paradigms and Case Studies. 37. Machine Learning in Agriculture.

Über Autor(innen)

Abhishek Kumar is Doctorate in computer science from University of Madras and done M.tech in Computer Sci. & Engineering from Government engineering college Ajmer, Rajasthan Technical University, Kota India. He has total Academic teaching experience of more than 7 years with more than 80 publications in reputed, peer reviewed National and International Journals, books & Conferences. He has guided more than 20 M.Tech Projects and Thesis and guiding 2 PhD Scholar. His research area includes- Artificial intelligence, Image processing, Computer Vision, Data Mining, Machine Learning. He has been Session chair and keynote Speaker of many International conferences, webinars in India and Abroad. He has been the reviewer for IEEE and Inderscience Journal. He has authored/Co-Authored 6 books published internationally and edited 16 book (Published & ongoing with Elsevier, Wiley, IGI GLOBAL Springer, Apple Academic Press, De-Grueter and CRC etc. He has been member of various National and International professional societies in the field of engineering & research like Senior Member of IEEE, IAENG (International Association of Engineers), Associate Member of IRED (Institute of Research Engineers and Doctors), He has got Sir CV Raman National award for 2018 in young researcher and faculty Category from IJRP Group. He is Editor of Special issue in the Journal Computer materials and continua [SCI and SCOPUS.IF- 4.98] and Intelligent Automation and Soft Computing [SCI, SCOPUS, IF-1.276] Cognitive Neuro dynamics, Springer [SCI, SCOPUS, IF-3.925].

Ashutosh Kumar Dubey PhD is currently in the department of Computer Science and Engineering, Chitkara University School of Engineering and Technology, Chitkara University, Himachal Pradesh, India. He received his PhD degree in Computer Science and Engineering from JK Lakshmipat University, Jaipur, and Rajasthan, India. He is the Senior Member of IEEE and ACM. He has more than 14 years of teaching experience. He has authored a book name Database Management Concepts. He has been associated with many international and national conferences as the Technical Program Committee member. He is also associated as the Editor/Editorial Board Member/ Reviewer of many peer-reviewed journals. His research areas are Data Mining, Health Informatics, Optimization, Machine Learning, Cloud Computing, Artificial Intelligence and Object-Oriented Programming.

Sreenatha G. Anavatti is a Senior Lecturer with the School of Engineering and Information Technology at the University of New South Wales, Canberra, Australia. He has a Ph.D. from Indian Institute of Science, Bengaluru, India. Before moving to Australia, he was an Associate Professor at Indian Institute of Technology, Mumbai, India. As an established faculty at Indian Institute of Technology, he has contributed to the major National Projects like Indian Remote Sensing Satellite, Light Combat Aircraft and Air to Air Missile. His research work includes the application of AI for autonomous systems that include image processing for improved sensing and GAN based networks for improved classification with imbalanced data sets. In addition, he also works on the application of modern control tools for applications related to Aerospace, Underwater and Ground Vehicles including Evolutionary Fuzzy and Fuzzy Neural Systems for identification and control of dynamic systems. He has authored more than 250 papers in peer reviewed International Journals and International conferences. He has been an active reviewer for a number of high quality journals like IEEE transactions and Technical Committee member for a number of International Conferences like SSCI

Pramod Singh Rathore is pursuing his Doctorate in computer science from University of Engineering and Management (UEM) and done M. Tech in Computer Sci. & Engineering from Government engineering college Ajmer, Rajasthan Technical University, Kota India. He has been working as an Assistant professor of Computer Science & Engineering Department at Aryabhatt Engineering College and Research centre, Ajmer, Rajasthan and also visiting faculty in Government University MDS Ajmer. He has total Academic teaching experience of more than 8 years with more than 50 publications in reputed, peer reviewed National and International Journals, books & Conferences like Wiley, IGI GLOBAL, Taylor & Francis Springer, Elsevier Science Direct, Annals of Computer Science, Poland, and IEEE. He has authored/Co-Authored 6 books published internationally and edited 16 book (Published & ongoing with Elsevier, Wiley, IGI GLOBAL Springer, Apple Academic Press, De-Grueter and CRC etc. His research area includes NS2, Computer Network, Mining, and DBMS.