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Identifying diseases that cause psychological trauma and social avoidance by Xgboost

机译:通过Xgboost识别导致心理创伤和社会回避的疾病

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With the development of modern medical technology, the survival time of patients with most diseases is significantly prolonged. Changes in the physical, psychological, and social functions that occur after treatment and during treatment are a serious problem for patients and their families. Under the guidance of bio-psycho-social medical model theory, patients need not only disease care, but also mental health. Therefore, identifying diseases that can cause psychological trauma and social avoidance will provide great guidance for medical staff and greatly improve the quality of life of patients. In this paper, Xgboost is introduced to identify diseases that cause psychological trauma and social avoidance. Firstly, the diseases are known to cause psychological problems are extracted from literatures, and then the relevant diseases are extracted in the Disease Ontology (DO), and finally the proteins corresponding to each disease are obtained from Uniprot. We encoded proteins as the feature of each disease and put them into Xgboost. Finally, we identified the diseases that cause psychological trauma and social avoidance. Leave-one-out cross validation has been introduced to test the performance of Xgboost. We achieved AUC 0.95 and 0.61 AUPR. In addition, several case studies have been done to prove the accuracy of our result.
机译:随着现代医疗技术的发展,大多数疾病患者的生存时间大大延长。治疗后和治疗期间发生的身体,心理和社会功能的变化对于患者及其家人而言是一个严重的问题。在生物心理社会医学模型理论的指导下,患者不仅需要疾病护理,还需要心理健康。因此,发现可能导致心理创伤和社会回避的疾病将为医护人员提供指导,并极大地改善患者的生活质量。本文介绍了Xgboost来识别导致心理创伤和社会回避的疾病。首先,从文献中提取已知会导致心理问题的疾病,然后在疾病本体论(DO)中提取相关疾病,最后从Uniprot获得与每种疾病相对应的蛋白质。我们将蛋白质编码为每种疾病的特征,然后将它们放入Xgboost。最后,我们确定了导致心理创伤和社会回避的疾病。引入了留一法交叉验证来测试Xgboost的性能。我们实现了0.95的AUC和0.61的AUPR。此外,已经进行了一些案例研究,以证明我们的结果的准确性。

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