vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff7bce31000000af4e010001000200 Nanotechnology is an emerging technology that has been used in a variety of fields, such as medicine, biology, and medicine. In this article, we analyze a deep learning (DL) that has the potential to revolutionize the future generation of medication delivery, as well as the three problems that need to be overcome in order to make discriminative and generative nanotechnology a viable source of continuous innovation. In addition, we discuss the three obstacles that must be overcome to make DL a sustainable source of innovation. We believe that these machine learning models, which may become available in the short to medium term, will have an influence on nanotechnology for healthcare. The research is able to capitalize on the enormous potential offered by nanotechnology. It is projected that the beginning of a new century in the field of nanotechnology research will be defined by the production of predictive models and the de novo design of composite nano-delivery systems.
M. Srinivasan1, S. Vanarasan2, Kogila Palanimuthu3, Vinod N. Alone4
P.S.V College of Engineering and Technology, India1,2, Dambi Dollo University, Ethiopia3, Vasantdada Patil Pratishthan’s College of Engineering and Visual Arts, India4
Deep Learning, Nanotechnology, Healthcare, Real-Time, Mechanism
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| Published By :
ICTACT
Published In :
ICTACT Journal on Microelectronics
( Volume: 9 , Issue: 1 , Pages: 1517 - 1520 )
Date of Publication :
April 2023
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730
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