Prediction

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Resilience risk prediction model for schizophrenia​

An Online Calculator based on minor physical anomalies variables
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A risk prediction model based on machine learning algorithms and nomograms was used to predict the risk of resilience using qualitative and quantitative minor physical anomalies in schizophrenia patients. The predictors of the model were identified by feature selection algorithms based on varSelRF.




DNA Methylation

cg18565204
cg17682313
cg07167608
cg03013609


Gray Matter Volume

fusiform (rh)
inferiorparietal (rh)
rostralmiddlefrontal (rh)
temporalpole (rh)
bankssts (lh)
caudalanteriorcingulate (lh)
fusiform (lh)
inferiorparietal (lh)
lingual (lh)
middletemporal (lh)
parahippocampal (lh)
precentral (lh)
rostralmiddlefrontal (lh)

Diffusion Tensor Imaging

CH_L (FA)
CST_L (FA)
Fmaj (FA)
SLF_R (FA)
CH_R (RD)




× Disclaimer:
Results from the calculator should only be used in conjunction with all other clinical information on each case and only for research.
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Sheng-Hsiang Lin, Ph.D. 
Laboratory of Genetic Psychiatric Epidemiology and Biostatistics
​Institute of Clinical Medicine
​National Cheng Kung University   
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[email protected]  

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Copyright © 2024 Dr. Sheng-Hsiang Lin. All rights reserved.