Title
A Study Of A Health Resources Management Platform Integrating Neural Networks And Dss Telemedicine For Homecare Assistance
Abstract
The proposed paper is related to a case of study of an e-health telemedicine system oriented on homecare assistance and suitable for de-hospitalization processes. The proposed platform is able to transfer efficiently the patient analyses from home to a control room of a clinic, thus potentially reducing costs and providing high-quality assistance services. The goal is to propose an innovative resources management platform (RMP) integrating an innovative homecare decision support system (DSS) based on a multilayer perceptron (MLP) artificial neural network (ANN). The study is oriented in predictive diagnostics by proposing an RMP integrating a KNIME (Konstanz Information Miner) MLP-ANN workflow experimented on blood pressure systolic values. The workflow elaborates real data transmitted via the cloud by medical smart sensors and provides a prediction of the patient status. The innovative RMP-DSS is then structured to enable three main control levels. The first one is a real-time alerting condition triggered when real-time values exceed a threshold. The second one concerns preventative action based on the analysis of historical patient data, and the third one involves alerting due to patient status prediction. The proposed study combines the management of processes with DSS outputs, thus optimizing the homecare assistance activities.
Year
DOI
Venue
2018
10.3390/info9070176
INFORMATION
Keywords
Field
DocType
homecare assistance management, smart health, e-health, telemedicine architecture, artificial neural network, multilayer perceptron, patient health status prediction, KNIME
Resource management,Telemedicine,Software engineering,Computer science,Decision support system,Multilayer perceptron,Artificial intelligence,Control room,Artificial neural network,Workflow,Machine learning,Cloud computing
Journal
Volume
Issue
Citations 
9
7
1
PageRank 
References 
Authors
0.43
5
7