Towards a Complex Evolutionary Agent-Based System for Medical Sensor Data

被引：0

作者：

Dinis, Adriana ^{[1
]}

Ivascu, Todor ^{[1
]}

Negru, Viorel ^{[1
]}

机构：

[1] West Univ Timisoara, Dept Comp Sci, Fac Math & Informat, Bvd V Parvan 4, Timisoara, Romania

来源：

2017 19TH INTERNATIONAL SYMPOSIUM ON SYMBOLIC AND NUMERIC ALGORITHMS FOR SCIENTIFIC COMPUTING (SYNASC 2017) | 2017年

关键词：

Evolutionary Multi-agent System; Ambient Intelligence; Smart Hospital; Genetic Algorithms; Machine Learning;

D O I：

10.1109/SYNASC.2017.00064

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Various gadgets and medical devices collect data from patients continuously. Processing this information and learning from it is a challenge for data scientists as this kind of data comes in complex and large quantities, making the decision of what kind of algorithms to apply for the best results difficult and time consuming. In this paper we propose a Multi-agent system that enables autonomous selection and application of machine learning methods for data sets belonging to medical systems, by applying genetic algorithms to agents.

引用

页码：356 / 360

页数：5

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