首页|Medical Psychological Center Reports Findings in Major Depressive Disorder (Pred ictive modeling of antidepressant efficacy based on cognitive neuropsychological theory)
Medical Psychological Center Reports Findings in Major Depressive Disorder (Pred ictive modeling of antidepressant efficacy based on cognitive neuropsychological theory)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Major Depressive Disor der is the subject of a report. According to news originating from Changsha, Peo ple's Republic of China, by NewsRx correspondents, research stated, "We aimed to develop a clinical predictive model based on the cognitive neuropsychological ( CNP) theory and machine-learning to examine SSRI efficacy in the treatment of MD D. Baseline assessments including clinical symptoms (HAMD, HAMA, BDI, and TEPS s cores), negative biases (NEO-PI-R-N and NCPBQ scores), sociodemographic characte ristics (social support and SES), and a 5-min eye-opening resting-state EEG were completed by 69 participants with first-episode major depressive disorder (MDD) and 36 healthy controls." Our news journalists obtained a quote from the research from Medical Psychologic al Center, "The clinical symptoms and negative bias were again assessed after an 8-week treatment of depression with selective serotonin reuptake inhibitors (SS RIs). A multi-modality machine-learning model was developed to predict the effec tiveness of SSRI antidepressants. At baseline, we observed significant differenc es between MDD patients and healthy controls in terms of social support, clinica l symptoms, and negative bias characteristics (p <0.001). A negative association was found (p <0.05) between neuroti cism and alpha asymmetry in both the central and central-parietal areas, as well as between negative cognitive processing bias and alpha asymmetry in the pariet al region. Compared to responders, non-responders exhibited less negative cognit ive processing bias and greater alpha asymmetry in both central and centralpari etal regions. Importantly, we developed a multi-modality machine-learning model with 83 % specificity using the above salient features. Research r esults support the CNP theory of depression treatment. To some extent, the multi modal clinical model constructed based on the CNP theory effectively predicted t he efficacy of this treatment in this population."
ChangshaPeople's Republic of ChinaAs iaCyborgsDrugs and TherapiesEmerging TechnologiesHealth and MedicineMa chine LearningMajor Depressive Disorder
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