Technical Access in Blood Glucose Detection using ANN
F. Emerson Solomon1, R. Kishore Kanna2, Vasukidevi Ramachandran3, S. Geetha4
1Dr. F. Emerson Solomon, Deptmant Of Biomedical Engg, BIHER, Chennai, Tamilnadu, India.
2R. Kishore Kanna, Deptmant Of Biomedical Engg, BIHER, Chennai, Tamilnadu, India.
3Dr. Vasukidevi Ramachandran, Deptmant Of Biomedical Engg, BIHER, Chennai, Tamilnadu, India.
4S. Geetha, Deptmant Of Biomedical Engg, BIHER, Chennai, Tamilnadu, India.
Manuscript received on 09 August 2019 | Revised Manuscript received on 16 August 2019 | Manuscript Published on 31 August 2019 | PP: 332-335 | Volume-8 Issue-9S2 August 2019 | Retrieval Number: I10700789S219/19©BEIESP DOI: 10.35940/ijitee.I1070.0789S219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
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.
Keywords: Artificial Neural Network, Multilayer Perception, Logistic Regression
Scope of the Article: Artificial Intelligence and Machine Learning