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Machine Learning-Based Identification of Suicidal Risk in Patients With Schizophrenia Using Multi-Level Resting-State fMRI Features

机译：利用多级休息状态FMRI特征的精神分裂症患者自杀风险的机器鉴定

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Bartosz Bohaterewicz; Anna M. Sobczak; Igor Podolak; Bartosz Wójcik; Dagmara Mȩtel; Adrian A. Chrobak; Magdalena Fa̧frowicz; Marcin Siwek; Dominika Dudek; Tadeusz Marek;
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1. Classification of schizophrenia patients on lattice computing resting-state fMRI features [J] . Chyzhyk Darya, Grana Manuel Neurocomputing . 2015,第mara3pta1期

机译：基于晶格计算静止状态功能磁共振成像特征的精神分裂症患者分类
2. Schizophrenic patient identification using graph-theoretic features of resting-state fMRI data [J] . Algunaid Rami F., Algumaei Ali H., Rushdi Muhammad A., Biomedical signal processing and control . 2018,第MAY期

机译：使用静息状态fMRI数据的图论特征识别精神分裂症患者
3. Identification of risk factors for suicidal ideation in patients with schizophrenia [J] . Fang Xinyu, Yan Chen, Wang Yewei, Psychiatry research . 2019,第期

机译：精神分裂症患者自杀素识别危险因素的鉴定
4. Accurate classification of schizophrenia patients based on novel resting-state fMRI features [C] . Arbabshirani Mohammad R., Castro Eduardo, Calhoun Vince D. Annual International Conference of the IEEE Engineering in Medicine and Biology Society . 2014

机译：基于新的静止状态功能磁共振成像特征对精神分裂症患者进行准确分类
5. Investigation of Discrepancies in Brain Effective Connectivity Between Healthy Control and Epileptic Patient Groups: A Resting-State fMRI Study [D] . Mahalingam, Neeraja 2019

机译：健康控制和癫痫患者组之间的大脑有效连通性差异研究：静态fMRI研究
6. Machine Learning-Based Identification of Suicidal Risk in Patients With Schizophrenia Using Multi-Level Resting-State fMRI Features [O] . Bartosz Bohaterewicz, Anna M. Sobczak, Igor Podolak, 2020

机译：利用多级休息状态FMRI特征的精神分裂症患者自杀风险的机器鉴定
7. Enhancing Multi-Center Generalization of Machine Learning-Based Depression Diagnosis From Resting-State fMRI [O] . Takashi Nakano, Masahiro Takamura, Naho Ichikawa, 2020

机译：从休息状态FMRI加强基于机器学习抑郁症的多中心概括

Machine Learning-Based Identification of Suicidal Risk in Patients With Schizophrenia Using Multi-Level Resting-State fMRI Features

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