Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics (eBook, PDF)

Redaktion: Kumar, Abhishek; Rathore, Pramod Singh; Anavatti, Sreenatha G.; Dubey, Ashutosh Kumar

• Format: PDF

Produktbeschreibung

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

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 240
• Erscheinungstermin: 9. März 2022
• Englisch
• ISBN-13: 9781000539974
• Artikelnr.: 63576142

Autorenporträt

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.

Inhaltsangabe

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.