@article{ref1,
title="Discovery of intentional self-harm patterns from suicide and self-harm surveillance reports",
journal="Healthcare informatics research",
year="2022",
author="Vichianchai, Vuttichai and Kasemvilas, Sumonta",
volume="28",
number="4",
pages="319-331",
abstract="OBJECTIVES: The purpose of this study was to identify patterns of self-harm risk factors from suicide and self-harm surveillance reports in Thailand. <br><br>METHODS: This study analyzed data from suicide and self-harm surveillance reports submitted to Khon Kaen Rajanagarindra Psychiatric Hospital, Thailand. The process of identifying patterns of self-harm risk factors involved: data preprocessing (namely, data preparation and cleaning, missing data management using listwise deletion and expectation-maximization techniques, subgrouping factors, determining the target factors, and data correlation for learning); classifying the risk of self-harm (severe or mild) using 10-fold cross-validation with the support vector machine, random forest, multilayer perceptron, decision tree, k-nearest neighbors, and ensemble techniques; data filtering; identifying patterns of self-harm risk factors using 10-fold cross-validation with the classification and regression trees (CART) technique; and evaluating patterns of self-harm risk factors. <br><br>RESULTS: The random forest technique was most accurate for classifying the risk of self-harm, with specificity, sensitivity, and F-score of 92.84%, 93.12%, and 91.46%, respectively. The CART technique was able to identify 53 patterns of self-harm risk, consisting of 16 severe self-harm risk patterns and 37 mild self-harm risk patterns, with an accuracy of 92.85%. In addition, we discovered that the type of hospital was a new risk factor for severe selfharm. <br><br>CONCLUSIONS: The procedure presented herein could identify patterns of risk factors from self-harm and assist psychiatrists in making decisions related to self-harm among patients visiting hospitals in Thailand.<p /> <p>Language: en</p>",
language="en",
issn="2093-3681",
doi="10.4258/hir.2022.28.4.319",
url="http://dx.doi.org/10.4258/hir.2022.28.4.319"
}