A neural network approach for marketing strategies research and decision support
A neural network approach for marketing strategies research and decision support
Machine Learning
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
PsyDis: Towards a diagnosis support system for psychological disorders
Expert Systems with Applications: An International Journal
A secure IRB system for assisting the development of intelligent medical devices
Expert Systems with Applications: An International Journal
Towards an ontology for psychological disorders
International Journal of Metadata, Semantics and Ontologies
| Hi-index | 12.05 |
Psychological distress and disabilities are increasingly identified among general population. Psychiatrist availability in rural areas is poor and often general practitioners have to identify and treat psychiatric problems like depression and anxiety. This work proposes a method to identify the psychiatric problems among patients using multimodel decision support system. Backpropagation neural networks (BPNN), radial basis function neural network (RBFNN) and support vector machine (SVM) models are used to design the decision support system. Forty-four factors are considered for feature extraction. The features are collected from 400 patients and divided into four sets of equal size. Three sets of patient features are used to train the decision support system and one set of patient feature are used to evaluate performance of the system. Experimental results show that the proposed method achieves an accuracy of 98.75% for identifying the psychiatric problems.