■年轻人的心理健康问题处于所有发展和可能性的门槛。强迫症(OCD),分离焦虑症(SAD),注意缺陷多动障碍(ADHD)是影响儿童和青少年的三种最常见的精神疾病。已经对识别强迫症的方法进行了几项研究,SAD和ADHD,但是由于功能和参与者有限,它们的准确性不足。因此,这项研究的目的是研究使用机器学习(ML)算法的方法,该算法具有澳大利亚全国代表性的儿童和青少年心理健康调查的1474个特征。
■基于基于树的管道优化工具(TPOTClassifier)的内部交叉验证(CV)得分,数据集已经使用三个最优算法进行了检查,包括随机森林(RF),决策树(DT)和高斯朴素贝叶斯(GaussianNB)。
■GaussianNB在OCD分类方面表现良好,准确率为91%,精度为76%,和96%的特异性以及检测SAD的79%的准确性,精度为62%,91%的特异性。射频在识别ADHD方面优于所有其他方法,准确率为91%,94%的精度,99%的特异性。
■根据分析结果,使用Streamlit和Python开发了一个Web应用程序。该应用程序将帮助父母/监护人和学校官员在儿童和青少年早期使用体征和症状检测精神疾病,以便尽早开始治疗。
UNASSIGNED: Mental health issues of young minds are at the threshold of all development and possibilities. Obsessive-compulsive disorder (OCD), separation anxiety disorder (SAD), and attention deficit hyperactivity disorder (ADHD) are three of the most common mental illness affecting children and adolescents. Several studies have been conducted on approaches for recognising OCD, SAD and ADHD, but their accuracy is inadequate due to limited features and participants. Therefore, the purpose of this study is to investigate the approach using machine learning (ML) algorithms with 1474 features from Australia\'s nationally representative mental health survey of children and adolescents.
UNASSIGNED: Based on the internal cross-validation (
CV) score of the Tree-based Pipeline Optimization Tool (TPOTClassifier), the dataset has been examined using three of the most optimal algorithms, including Random Forest (RF), Decision Tree (DT), and Gaussian Naïve Bayes (GaussianNB).
UNASSIGNED: GaussianNB performs well in classifying OCD with 91% accuracy, 76% precision, and 96% specificity as well as in detecting SAD with 79% accuracy, 62% precision, 91% specificity. RF outperformed all other methods in identifying ADHD with 91% accuracy, 94% precision, and 99% specificity.
UNASSIGNED: Using Streamlit and Python a web application was developed based on the findings of the analysis. The application will assist parents/guardians and school officials in detecting mental illnesses early in their children and adolescents using signs and symptoms to start the treatment at the earliest convenience.