Prediction of the period of psychotic episode in individual schizophrenics by simulation-data construction approach.
Although schizophrenia can be treated, most patients still experience inevitable psychotic episodes from time to time. Precautious actions can be taken if the next onset can be predicted. However, sufficient information is always lacking in the clinical scenario. A possible solution is to use the virtual data generated from limited of original data. Data construction method (DCM) has been shown to generate the virtual felt earthquake data effectively and used in the prediction of further events. Here we investigated the performance of DCM in deriving the membership functions and discrete-event simulations (DES) in predicting the period embracing the initiation and termination time-points of the next psychotic episode of 35 individual schizophrenic patients. The results showed that 21 subjects had a success of simulations (RSS) ≥70%. Further analysis demonstrated that the co-morbidity of coronary heart diseases (CHD), risks of CHD, and the frequency of previous psychotic episodes increased the RSS.
Huang
Chun-Jung
CJ
Department of Industrial Engineering and Engineering Management, College of Engineering, National Tsing-Hua University, HsinChu, Taiwan.
Wang
Hsiao-Fan
HF
Chiu
Hsien-Jane
HJ
Lan
Tsuo-Hung
TH
Hu
Tsung-Ming
TM
Loh
El-Wui
el-W
D000465:Algorithms; D003198:Computer Simulation; D003661:Decision Support Techniques; D005260:Female; D005544:Forecasting; D006801:Humans; D008297:Male; D008875:Middle Aged; D012008:Recurrence; D015203:Reproducibility of Results; D012559:Schizophrenia / Q000175:diagnosis*