Rashmi (Hrsg.) Agrawal
Machine Learning for Healthcare
Handling and Managing Data
Ebook (PDF Format)
Machine Learning for Healthcare: Handling and Managing Data provides in-depth information about handling and managing healthcare data through machine learning methods. This book expresses the long-standing challenges in healthcare informatics and provides rational explanations of how to deal with them.Machine Learning for Healthcare: Handling and Managing Data provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of machine learning applications. These are illustrated in a case study which examines how chronic disease is being redefined through patient-led data lea…
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Beschreibung
Machine Learning for Healthcare: Handling and Managing Data provides in-depth information about handling and managing healthcare data through machine learning methods. This book expresses the long-standing challenges in healthcare informatics and provides rational explanations of how to deal with them.Machine Learning for Healthcare: Handling and Managing Data provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of machine learning applications. These are illustrated in a case study which examines how chronic disease is being redefined through patient-led data learning and the Internet of Things. This text offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare. Readers will discover the ethical implications of machine learning in healthcare and the future of machine learning in population and patient health optimization. This book can also help assist in the creation of a machine learning model, performance evaluation, and the operationalization of its outcomes within organizations. It may appeal to computer science/information technology professionals and researchers working in the area of machine learning, and is especially applicable to the healthcare sector.The features of this book include:A unique and complete focus on applications of machine learning in the healthcare sector.An examination of how data analysis can be done using healthcare data and bioinformatics.An investigation of how healthcare companies can leverage the tapestry of big data to discover new business values. An exploration of the concepts of machine learning, along with recent research developments in healthcare sectors.
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Produktdetails
Weitere Autoren: Chatterjee, Jyotir Moy (Hrsg.) / Kumar, Abhishek (Hrsg.) / Rathore, Pramod Singh (Hrsg.) / Le, Dac-Nhuong (Hrsg.)
- ISBN: 978-1-00-022178-7
- EAN: 9781000221787
- Produktnummer: 34256801
- Verlag: Taylor & Francis Ltd.
- Sprache: Englisch
- Erscheinungsjahr: 2020
- Seitenangabe: 222 S.
- Plattform: PDF
- Masse: 15'881 KB
- Auflage: 1. Auflage
- Abbildungen: 92 schwarz-weiße Abbildungen
Über den Autor
Dac-Nhuong Le is Ph.D, Deputy-Head of Faculty of Information Technology, Haiphong University, Vietnam. Vice-Director of Information Technology Apply Center in the same university. He is a research scientist of Research and Development Center of Visualization & Simulation in (CSV), Duy Tan University, Danang, Vietnam. He has more than 45 publications in the reputed international conferences, journals and online book chapter contributions (Indexed By: SCI, SCIE, SSCI, Scopus, ACM, DBLP). His area of research includes: evaluation computing and approximate algorithms, network communication, security and vulnerability, network performance analysis and simulation, cloud Computing, image processing in biomedical. His core work in network security, wireless, soft computing, mobile computing and biomedical. Recently, he has been the technique program committee, the technique reviews, the track chair for international conferencesJyotir Moy Chatterjee is currently working as an Assistant Professor of IT department at LBEF (Asia Pacific University of Technology & Innovation), Kathmandu, Nepal. Prior to that he worked as an Assistant Professor in CSE department at GD Rungta College of Engineering & Technology (CSVTU), Bhilai, Chhattisgarh, India. He has completed M. Tech in Computer Science & Engineering from Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha and B. Tech in Computer Science & Engineering from Dr. MGR Educational & Research Institute, Chennai. He is having 33 publications (3 SCIE indexed, 1 SCI indexed, 1 ESCI indexed, 1 ACMDL indexed, 1 Web of Science indexed, 23 UGC indexed, 2 International Conference, 1 authored book, 2 Scopus indexed book chapter). His research interest includes the Cloud Computing, Big Data, Privacy Preservation, Data Mining, Internet of Things, Machine Learning.Abhishek Kumar Pandey is pursuing his Doctorate in computer science from University of Madras and got enrolled in 2015 session and researching on face recognition using IOT concept and completed M. Tech in Computer Sci. & Engineering from Government engineering college Ajmer, Rajasthan Technical University, Kota India. He is working as an Assistant Professor of Computer Science at Aryabhatt Engineering College and Research centre, Ajmer and also visiting faculty in Government University MDS Ajmer.Rashmi Agrawal is working as Professor in Department of Computer Applications in MRIIRS, Faridabad. She has a rich teaching experience of more than 17 years. She is UGC-NET(CS) qualified.
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