首页|Hospital Beatriz Angelo Reports Findings in Psychosis (Machine Learning in Elect roconvulsive Therapy: A Systematic Review)
Hospital Beatriz Angelo Reports Findings in Psychosis (Machine Learning in Elect roconvulsive Therapy: A Systematic Review)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Mental Health Diseases and Conditions - Psychosis is the subject of a report. According to news report ing originating from Lisbon, Portugal, by NewsRx correspondents, research stated , "Despite years of research, we are still not able to reliably predict who migh t benefit from electroconvulsive therapy (ECT) treatment. As we exhaust what is possible using traditional statistical analysis, ECT remains a good candidate fo r machine learning approaches due to the large data sets with data captured thro ugh electroencephalography (EEG) and other objective measures." Our news editors obtained a quote from the research from Hospital Beatriz Angelo , "A systematic review of 6 databases led to the full-text examination of 26 art icles using machine learning approaches in examining data predicting response to ECT treatment. The identified articles used a wide variety of data types coveri ng structural and functional imaging data (n = 15), clinical data (n = 5), a com bination of clinical and imaging data (n = 2), EEG (n = 3), and social media pos ts (n = 1). The clinical indications in which response prediction was assessed w ere depression (n = 21) and psychosis (n = 4). Changes in multiple anatomical re gions in the brain were identified as holding a predictive value for response to ECT. These primarily centered on the limbic system and associated networks. Cli nical features predicting good response to ECT in depression included shorter du ration, lower severity, higher medication dose, psychotic features, low cortisol levels, and positive family history. It has also been possible to predict the l ikelihood of relapse of readmission with psychosis after ECT treatment, includin g a better response if higher transfer entropy was calculated from EEG signals."
LisbonPortugalEuropeCyborgsDiagn ostics and ScreeningElectroconvulsive TherapyElectroencephalographyEmergin g TechnologiesHealth and MedicineMachine LearningMental Health Diseases an d ConditionsNeurologyPharmaceuticalsPsychosisTherapy
NETL
NSTL
