• 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.

Minor Physical Variables

Eyes region

Ears region

Mouth region

Facial width

Upper facial height

Interpupillary distance

Slant of the palpebral fissure

Analyze Facial Features

Prediction Probability

0%

Feature Importance Analysis

Disclaimer: Results from the calculator should only be used in conjunction with all other clinical information on each case and only for research..

Sheng-Hsiang Lin, Ph.D.
Laboratory of Genetic Psychiatric Epidemiology and Biostatistics
Institute of Clinical Medicine
National Cheng Kung University
Tainan, Taiwan
[email protected]

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Copyright © 2025 Dr. Sheng-Hsiang Lin. All rights reserved.