Machine Learning for Healthcare: Handling and Managing Data

.Machine Learning for HealthcareHandling and Managing DataMachine 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 guideddiscover 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.Read MoreAdditional ISBNs9780367352332, 9780367625719, 9780429330131Machine Learning for Healthcare: Handling and Managing Data 1st Edition is written by DacNhuong Le; Abhishek KUMAR; Rashmi Agrawal and published by Chapman & Hall. ISBNs for Machine Learning for Healthcare are 9781000221886, 1000221881 and the print ISBNs are 9780367816896, 036781689X. Additional ISBNs include 9780367352332, 9780367625719, 9780429330131.