Technical access in blood glucose detection using ANN

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Abstract

Early re-affirmation of patients builds the expense of human services and it exceptionally impacts the notoriety of the clinic. Discovering readmission in essential stage, enables the clinics to give extraordinary consideration for those patients, and after that can lessen the rate of readmission. In this work build up another model utilizing profound learning. It is the correlation technique between AI and profound learning. Typically, Logistic relapse is utilized for all sort of expectation. Be that as it may, as per this information fake neural system model in profound learning give promising outcome than strategic relapse.

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Solomon, F. E., Kanna, R. K., Ramachandran, V., & Geetha, S. (2019). Technical access in blood glucose detection using ANN. International Journal of Innovative Technology and Exploring Engineering, 8(9 Special Issue 2), 332–335. https://doi.org/10.35940/ijitee.I1070.0789S219

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