Text Analysis in Health Care Study Using IoT

Kazi Kutubuddin Sayyad Liyakat

Abstract

The Internet of Things (IoT) should be a recent buzzword that has steadily acquired acceptance (IoT). Organizations, governments, and the scientific community have already acknowledged the significance of the Internet of Things as a result of a surge in publications over the past few years. Despite scant research on goals and potential breakthroughs, IoT in health had a significant role in this development. In this study, the only method used to evaluate the long-term trends of IoT devices' use in medicine is data mining and bibliometric analysis. Between 2000 and 2021, 778 entries were taken from the Web of Science. The 30 sets of publications that were divided up by abstract text data were showed eight IoT in health trends. The technique of extracting valuable information from supervised or unsupervised language material is known as textual classification. The techniques used in this procedure can be used for a variety of objectives and are transferable to other material categories, including research articles, information extraction, response assessment, and current fashion evaluation. The study's results were limited but meant to be inclusive. The analysis may have neglected publications in academic databases or articles that are now published. Many keyword combinations can yield a variety of research suggestions that have an impact on IoT in health trends.

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