Prospective End-to-End Internet of Bio-Nano Things Network Based in a Machine Learning Algorithm To Restore the Flux of Insuline in Prediabetic Patients

被引：0

作者：

Nieto-Chaupis, Huber ^{[1
]}

机构：

[1] Univ Privada Norte, Res Off, Campus Los Olivos,Av Alfredo Mendiola 6062, Lima 15306, Peru

来源：

2019 IEEE CHILEAN CONFERENCE ON ELECTRICAL, ELECTRONICS ENGINEERING, INFORMATION AND COMMUNICATION TECHNOLOGIES (CHILECON) | 2019年

关键词：

Beta Cells; Machine Learning; Internet of Bio-Nano Things;

D O I：

10.1109/chilecon47746.2019.8988030

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We present a physics-based theory and its computational simulation on the performance of a prospective nanodevice based on Machine Learning inside of an Internet of Bio-Nano Things networking to carry out the optimization of artificial incoming of Calcium2+ ions in beta cells aimed to push out granules of insulin. Although the engineered nanodevices can carry out an optimal task, the inclusion of a Machine Learning algorithm would guarantee the wellness as to avoid scenarios where nanodevices might be running with highest systematic errors.

引用

页数：4

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