基于认知测试的决策树分析在精神分裂症鉴别诊断中的应用

IF 2.5 4区 医学 Q2 PSYCHIATRY European Journal of Psychiatry Pub Date : 2022-10-01 DOI:10.1016/j.ejpsy.2022.05.003
Wentian Dong , Yong He , Jiuju Wang , Chuan Shi , Qihui Niu , Haokui Yu , Jun Ji , Xin Yu
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引用次数: 1

摘要

背景与目的探讨基于认知测试数据的决策树模型对精神分裂症的鉴别诊断能力。方法本研究纳入82例精神分裂症患者和82例情感障碍患者。两组参与者的认知功能是根据学习、符号编码、数字跨度、线索制作和类别流畅性测试进行评估的。应用Python中sklearn包中的逻辑回归模型来区分和分析MATRICS共识认知电池(MCCB)中所有11个变量的数据。结果应用MCCB的所有11个变量对精神分裂症和情感障碍的识别率为82%。结论基于认知数据的物流模型将精神分裂症患者与情感障碍患者区分开来。
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Differential diagnosis of schizophrenia using decision tree analysis based on cognitive testing

Background and objectives

To explore the discriminatory ability of a decision tree model based on cognitive testing data for the differential diagnosis of schizophrenia.

Methods

This study enrolled 82 patients with schizophrenia and 82 patients with affective disorders. The cognitive function of the two groups of participants was assessed based on learning, symbol coding, digital span, trail making, and category fluency tests. The logistic regression model in the sklearn package in Python was applied to discriminate and analyse the data for all 11 variables in the MATRICS Consensus Cognitive Battery (MCCB).

Results

The recognition rate for schizophrenia and affective disorder using all 11 variables of the MCCB was 82%.

Conclusion

The logistics model based on cognitive data distinguished patients with schizophrenia from those with affective disorder.

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来源期刊
CiteScore
2.90
自引率
0.00%
发文量
40
审稿时长
43 days
期刊介绍: The European journal of psychiatry is a quarterly publication founded in 1986 and directed by Professor Seva until his death in 2004. It was originally intended to report “the scientific activity of European psychiatrists” and “to bring about a greater degree of communication” among them. However, “since scientific knowledge has no geographical or cultural boundaries, is open to contributions from all over the world”. These principles are maintained in the new stage of the journal, now expanded with the help of an American editor.
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