A Concept of Applying Social Network Analysis in Medical Diagnosis

DOI

10.2991/csss-14.2014.15How to use a DOI?

Keywords

social network analysis; centrality; clustering; medical diagnosis;

Abstract

This paper aims to apply a social network analysis (SNA) to a medical diagnosis issue, which is the Caesarean sections due to Cephalopelvic disproportion (CPD). Firstly, the pregnant women, here is called “Patients”, are connected with each other by a medical examination consideration. The patients are also grouped based on medical pattern similarity. Secondly, the centrality measures in SNA, such as Degree, Hub or Authority, Closeness centrality, and Betweenness Centrality are applied to identify the cluster representative in each group of patients. To evaluate the proposed idea, the sample test of patients is conducted. The results show that hub or authority is taken to identify the cluster representative with minimal average distance between the test patient and existing groups, which is 0.684 by Euclidean distance. Finally, the medical diagnosis of test patient, here, is also acceptable by comparing to its real diagnosis by physician.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Sodsee Sunantha
AU  - Komkhao Maytiyanin
PY  - 2014/06
DA  - 2014/06
TI  - A Concept of Applying Social Network Analysis in Medical Diagnosis
BT  - Proceedings of the 3rd International Conference on Computer Science and Service System
PB  - Atlantis Press
SP  - 64
EP  - 67
SN  - 1951-6851
UR  - https://doi.org/10.2991/csss-14.2014.15
DO  - 10.2991/csss-14.2014.15
ID  - Sunantha2014/06
ER  -