Abstract
Due to the increase in many tools, the relevance of data analytics in health data systems has been growing tremendously as a result of this exponential increase. As a result, it has also led to renewed confidence in the development of data-oriented frameworks for sensor learning in health information systems. With funding provided by artificial neural networks, researchers are looking into the possibility of creating a flexible machine that redefines the recent vision of artificial intelligence. As computing power and rapid processing of reality have increased, the rapid return on technology has often been compromised in terms of conceptual control and production of highly functional and semi-relevant input details that are mechanically designed tails. In this paper, we provide an in-depth analysis of the relative relevance and potential downsides of the approach and its attitude as well as an advanced examination of fundamental learning in health information systems. Additionally, the paper discusses the challenges, security, and protection in healthcare systems with the use of machine learning approaches.
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Karthika, D., Deepika, M. (2023). A Review of Deep Learning Healthcare Problems and Protection Supports. In: Fong, S., Dey, N., Joshi, A. (eds) ICT Analysis and Applications. Lecture Notes in Networks and Systems, vol 517. Springer, Singapore. https://doi.org/10.1007/978-981-19-5224-1_41
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DOI: https://doi.org/10.1007/978-981-19-5224-1_41
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