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IoT Based Data Analytics for the Healthcare Industry: Techniques and Applications explores recent advances in the analysis of healthcare industry data through IoT data analytics… Read more
SUSTAINABLE DEVELOPMENT
Save up to 30% on top Physical Sciences & Engineering titles!
IoT Based Data Analytics for the Healthcare Industry: Techniques and Applications explores recent advances in the analysis of healthcare industry data through IoT data analytics. The book covers the analysis of ubiquitous data generated by the healthcare industry, from a wide range of sources, including patients, doctors, hospitals, and health insurance companies. The book provides AI solutions and support for healthcare industry end-users who need to analyze and manipulate this vast amount of data. These solutions feature deep learning and a wide range of intelligent methods, including simulated annealing, tabu search, genetic algorithm, ant colony optimization, and particle swarm optimization.
The book also explores challenges, opportunities, and future research directions, and discusses the data collection and pre-processing stages, challenges and issues in data collection, data handling, and data collection set-up. Healthcare industry data or streaming data generated by ubiquitous sensors cocooned into the IoT requires advanced analytics to transform data into information. With advances in computing power, communications, and techniques for data acquisition, the need for advanced data analytics is in high demand.
Researchers, academicians, and experts working in IoT in Health Industry, Health Management, Biomedical Engineering, Medical Applications, and Analysis, Application of Machine Learning and Deep Learning in Health, Big data-based learning techniques, Integrated approach of IoT and Artificial Intelligence for the Healthcare industry. Scientists, Researchers, Practitioners, Professionals from Government and Cloud-centric applications-based industries as well as Industries planning to deploy advanced analytics (DL) on Industrial Data
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