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Artificial Intelligence and Big Data Analytics for Smart Healthcare Next Generation Technology Driven Personalized Medicine And Smart Healthcare Series

Langue : Anglais

Coordonnateurs : Lytras Miltiadis, Sarirete Akila, Visvizi Anna, Chui Kwok Tai

Couverture de l’ouvrage 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.

Section 1: Big data infrastructure, framework and design for smart healthcareSection 2: Signal processing techniques for smart healthcare applicationsSection 3: Business analytics (descriptive, diagnostic, predictive and prescriptive) for smart healthcareSection 4: Emerging tools and techniques for smart healthcareSection 5: Challenges (e.g. security, privacy, and policy) in big data for smart healthcare. While in existing books, the focus is on limited areas (sections)Section 6: Appendixes
Clinicians, medical doctors, bioinformaticians
Miltiadis D. Lytras is an expert in advanced computer science and management, editor, lecturer, and research consultant, with extensive experience in academia and the business sector in Europe and Asia. Dr. Lytras is a Research Professor at Deree College - The American College of Greece and a Distinguished Scientist at the King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia. Dr. Lytras is a world-class expert in the fields of cognitive computing, information systems, technology enabled innovation, social networks, computers in human behavior, and knowledge management. In his work, Dr. Lytras seeks to bring together and exploit synergies among scholars and experts committed to enhancing the quality of education for all.
Dr. Akila Sarirete is Dean of Graduate Studies and Research at Effat University. She received her PhD degree in Computer Science and Knowledge Management. Her main research interests are in artificial intelligence, knowledge management, communities of practice, machine learning, big data, and service-oriented architectures. She presented her research work in several conferences in different countries. Dr. Sarirete has a vast experience in software development industry and software engineering. She is interested in engineering education, innovation, smart cities and villages especially, the human aspect and the collaborative work.
Anna Visvizi is an economist and political scientist, editor, and research and political consultant with extensive experience in academia, think tank and government sectors in Europe and the United States. Associate Professor at SGH Warsaw School of Economics, Warsaw, Poland, and Visiting Scholar at Effat University, Jeddah, Saudi Arabia, Professor Visvizi’s expertise covers issues pertinent to the intersection of politics, economics, and ICT. This translates in her research and advisory roles in the fields of AI and geopolitics, smart cities and smart villages, knowledge and innovation management, and technolog
  • 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

Date de parution :

Ouvrage de 290 p.

19x23.3 cm

Disponible chez l'éditeur (délai d'approvisionnement : 14 jours).

146,54 €

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Thème d’Artificial Intelligence and Big Data Analytics for Smart... :

Mots-clés :

?ADHD; Alzheimer’s disease; Applied data science; Architectural design; Artificial Intelligence; Artificial intelligence; Autism; Automatic identification system (AIS); Bibliometrics; Big data; Big data analytics; COVID-19; COVID-19 detection; CRISP-DM; Case study; Citation classification; Citation context analysis; Clinical decision support; Cloud computing; Cognitive assessment; Computing; Content analysis; Data analytics; Data mining; Data science; Deep learning; Design; Design science; Diabetes; Digital transformation; Disruption; Distributed computing; E-learning; EEG; Electronic patient records; Environmental health; Games in learning; Graph-based semisupervised learning; Health care; Health systems; Healthcare; Hospitals; Human voice; Hyperactivity; Hyperglycemia; Hypoglycemia; ICTs; Image classification; Imbalanced classification; Infection control; Influential citations; Interdisciplinary education; Internet of things; Internet of things (IoT); IoT; Labor; Learning approaches; Linear discriminant analysis; M-Health; MMSE; Machine learning; Manual dexterity; Maritime healthcare; Maritime risk estimation; Maritime safety; Medical diagnosis; Medical screening; Mild cognitive impairment; Mobile Partogram; Mobile application; Mobile cloud computing; Mobile health-care application; Mobile technology; Monitoring Parkinson’s disease; Monitoring system; Neurofeedback; Neurotherapy; One Health; Parkinson’s disease datasets; Parkinson’s symptoms digital test; Postpandemic solutions; Prediction model; Public health; Quality of life; Quality of service; Random forest; SARS-CoV-2; Saudi Commission for Health Specialties; Scientific literature; Scientometrics; Self-evaluation; Smart city; Smart healthcare; Smart living; Spatial memory test; Support vector machine; Surgical care; Surgical site infection; Text mining; Therapeutics