Cardiopulmonary Comorbidity, Radiomics and Machine Learning, and Therapeutic Regimens for a Cerebral fMRI Predictor Study in Psychotic Disorders

作     者：Xiao-Hui Wang Angela Yu Xia Zhu Hong Yin Long-Biao Cui 

作者机构：Department of Pulmonary and Critical Care Medicine The First Affiliated Hospital of Chongqing Medical University Chongqing 400016 China Department of Medicine Eastern Health Box Hill VIC 3128 Australia Department of Military Psychology School of Medical Psychology Fourth Military Medical University Xi’an 710032 China Department of Radiology Xijing Hospital Fourth Military Medical University Xi’an 710032 China Department of Clinical Psychology School of Medical Psychology Fourth Military Medical University Xi’an 710032 China 

出 版 物：《Neuroscience Bulletin》 (神经科学通报（英文版）)

年 卷 期：2019年第35卷第5期

页      面：955-957页

核心收录：

学科分类：10[医学] 

基　　金：supported by grants from the National Natural Science Foundation of China (81801675) the Military Medical Major Program during the Thirteenth Five-Year Plan Period of China (AWS17J012) 

主　　题：Cardiopulmonary Comorbidity Radiomics Machine Learning Psychotic Disorders 

摘      要：Recently, two researches by Doucet et al. and Collin et al. used functional neuroimaging as a tool to improve the management of schizophrenia and other psychotic disorders [1, 2]. We would like to highlight several issues in relation to cardiopulmonary comorbidity, radiomics and machine learning, and therapeutic regimens, along with their clinical implications.