Smart Healthcare Systems Using Data Science And Artificial Intelligence
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Artificial Intelligence and Big Data Analytics for Smart Healthcare
Artificial Intelligence and Big Data Analytics for Smart Healthcare serves as a key reference for practitioners and experts involved in healthcare as they strive to enhance the value added of healthcare and develop more sustainable healthcare systems. It brings together insights from emerging sophisticated information and communication technologies such as big data analytics, artificial intelligence, machine learning, data science, medical intelligence, and, by dwelling on their current and prospective applications, highlights managerial and policymaking challenges they may generate. The book is split into five sections: big data infrastructure, framework and design for smart healthcare; signal processing techniques for smart healthcare applications; business analytics (descriptive, diagnostic, predictive and prescriptive) for smart healthcare; emerging tools and techniques for smart healthcare; and challenges (security, privacy, and policy) in big data for smart healthcare. The content is carefully developed to be understandable to different members of healthcare chain to leverage collaborations with researchers and industry. - Presents a holistic discussion on the new landscape of data driven medical technologies including Big Data, Analytics, Artificial Intelligence, Machine Learning, and Precision Medicine - Discusses such technologies with case study driven approach with reference to real world application and systems, to make easier the understanding to the reader not familiar with them - Encompasses an international collaboration perspective, providing understandable knowledge to professionals involved with healthcare to leverage productive partnerships with technology developers
Smart Healthcare Systems
About the Book The book provides details of applying intelligent mining techniques for extracting & pre-processing medical data from various sources, for application-based healthcare research. Moreover, different datasets are used, thereby exploring real-world case studies related to medical informatics. This book would provide insight to the learners about Machine Learning, Data Analytics, and Sustainable Computing. Salient Features of the Book Exhaustive coverage of Data Analysis using R Real-life healthcare models for: Visually Impaired Disease Diagnosis & Treatment options Applications of Big Data & Deep Learning in Healthcare Drug Discovery Complete guide to learn the knowledge discovery process, build versatile real life healthcare applications Compare & analyze recent healthcare technologies and trends Target Audience This book is mainly targeted at researchers, undergraduate, postgraduate students, academicians, and scholars working in the area of data science and its application to health sciences. Also, the book is beneficial for engineers who are engaged in developing actual healthcare solutions. ng in Healthcare Drug Discovery Complete guide to learn the knowledge discovery process, build versatile real life healthcare applications Compare & analyze recent healthcare technologies and trends Target Audience This book is mainly targeted at researchers, undergraduate, postgraduate students, academicians, and scholars working in the area of data science and its application to health sciences. Also, the book is beneficial for engineers who are engaged in developing actual healthcare solutions.
Smart Healthcare Systems using Data Science and Artificial Intelligence
Author: Sweta
language: en
Publisher: Academic Guru Publishing House
Release Date: 2024-04-13
‘Smart Healthcare Systems Using Data Science & Artificial Intelligence’ is a comprehensive guidebook delving into the integration of cutting-edge technologies in healthcare. Authored by leading experts in the field, the book offers a meticulous exploration of how data science and artificial intelligence (AI) are revolutionizing healthcare delivery. Through a systematic approach, the book elucidates the myriad applications of data science and AI in healthcare, from patient diagnosis and treatment to operational efficiency and resource management. Readers gain insights into predictive analytics, machine learning algorithms, and deep learning techniques, all tailored to optimize patient care and streamline healthcare operations. Key topics covered include predictive modelling for early disease detection, personalized treatment plans based on patient data analysis, and AI-driven medical imaging for precise diagnoses. Moreover, the book addresses the ethical considerations and regulatory challenges inherent in deploying AI in healthcare, ensuring a balanced perspective on its implementation. With real-world case studies and practical examples, ‘Smart Healthcare Systems Using Data Science & Artificial Intelligence’ equips healthcare professionals, researchers, and policymakers with the knowledge and tools necessary to navigate the evolving landscape of smart healthcare. By harnessing the power of data and AI, the book paves the way for transformative advancements in healthcare delivery, ultimately improving patient outcomes and fostering a more efficient healthcare ecosystem.