Next Article in Journal
New Holographic Dark Energy Model in Brans-Dicke Theory
Next Article in Special Issue
Fuzzy Association Rule Based Froth Surface Behavior Control in Zinc Froth Flotation
Previous Article in Journal
An Intelligent Improvement of Internet-Wide Scan Engine for Fast Discovery of Vulnerable IoT Devices
Previous Article in Special Issue
Clickbait Convolutional Neural Network
Article Menu
Issue 5 (May) cover image

Export Article

Open AccessArticle
Symmetry 2018, 10(5), 152; https://doi.org/10.3390/sym10050152

Data Decision and Drug Therapy Based on Non-Small Cell Lung Cancer in a Big Data Medical System in Developing Countries

1,2,3,* , 4,* , 2,3
and
2,3
1
School of Information Science and Engineering, Central South University; Changsha 410083, China
2
“Mobile Health” Ministry of Education-China Mobile Joint Laboratory, Changsha 410083, China
3
School of Software, Central South University; Changsha 410083, China
4
PET-CT Center, the Second Xiangya Hospital of Central South University, Changsha 410083, China
*
Authors to whom correspondence should be addressed.
Received: 25 February 2018 / Revised: 23 April 2018 / Accepted: 9 May 2018 / Published: 10 May 2018
(This article belongs to the Special Issue Novel Machine Learning Approaches for Intelligent Big Data)
View Full-Text   |   Download PDF [2159 KB, uploaded 10 May 2018]   |  

Abstract

In many developing or underdeveloped countries, limited medical resources and large populations may affect the survival of mankind. The research for the medical information system and recommendation of effective treatment methods may improve diagnosis and drug therapy for patients in developing or underdeveloped countries. In this study, we built a system model for the drug therapy, relevance parameter analysis, and data decision making in non-small cell lung cancer. Based on the probability analysis and status decision, the optimized therapeutic schedule can be calculated and selected, and then effective drug therapy methods can be determined to improve relevance parameters. Statistical analysis of clinical data proves that the model of the probability analysis and decision making can provide fast and accurate clinical data. View Full-Text
Keywords: non-small cell lung cancer (NSCLC); data decision; drug therapy; relevance parameter non-small cell lung cancer (NSCLC); data decision; drug therapy; relevance parameter
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Wu, J.; Tan, Y.; Chen, Z.; Zhao, M. Data Decision and Drug Therapy Based on Non-Small Cell Lung Cancer in a Big Data Medical System in Developing Countries. Symmetry 2018, 10, 152.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Symmetry EISSN 2073-8994 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top