Machine learning and IoT applications for health informatics / editors, Pijush Samui Associate Professor, Department of Civil Engineering, Patna, Bihar, India, [and three others].

Other author Samui, Pijush, 1978-
Format Electronic
EditionFirst edition.
Publication InfoBoca Raton : CRC Press, Taylor & Francis Group, 2025.
Descriptionpages cm
Supplemental ContentFull text available from eBooks on EBSCOhost
Subjects

Abstract "Recently medical informatics, especially health informatics, has received various applications from machine learning and IoT. The applications of machine learning and IoT technology have wholly changed the predictive capability of the concerned disease. The input data to the machine learning and IoT-based devices are sometimes not structured. They could be unstructured as well; therefore, analyzing such unstructured data has significance. These data could be image related such as X-Ray images, ECG images, and others. Therefore, this edited book will focus on structure and unstructured data applications. Sickness and health-related data collection are also significant befinits of health analytics. Finally, further progress in the patients' health is made, and decisions are taken on further treatments based on the data. The Internet of Things (IoT) has emerged as a preferred solution to many emerging problems in the last few years. This colligated ecosystem in electronic devices can be worn as accessories and embedded in clothing. Also, the IoT-related apps have helped the data collection process and contributed to information technology. The interesting fact is that IoT applications can be found more in the healthcare system, especially healthcare informatics. IoT-powered applications in healthcare immensely benefit patients and physicians, hospitals, and overall healthcare systems. The wearables devices that are enabled with machine learning and IoT are changing the form of wearables like fitness bands, measuring blood pressure, and checking heart rate monitoring and glucometer concepts"-- Provided by publisher.
Bibliography noteIncludes bibliographical references and index.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
LCCN 2024022052
ISBN9781032544502 (hardcover)

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