RETRACTED ARTICLE: Classification of severe autism in fMRI using functional connectivity and conditional random forests
نویسندگان
چکیده
منابع مشابه
Identification of mild cognitive impairment disease using brain functional connectivity and graph analysis in fMRI data
Background: Early diagnosis of patients in the early stages of Alzheimer's, known as mild cognitive impairment, is of great importance in the treatment of this disease. If a patient can be diagnosed at this stage, it is possible to treat or delay Alzheimer's disease. Resting-state functional magnetic resonance imaging (fMRI) is very common in the process of diagnosing Alzheimer's disease. In th...
متن کاملAutism Classification Using Brain Functional Connectivity Dynamics and Machine Learning
The goal of the present study is to identify autism using machine learning techniques and resting-state brain imaging data, leveraging the temporal variability of the functional connections (FC) as the only information. We estimated and compared the FC variability across brain regions between typical, healthy subjects and autistic population by analyzing brain imaging data from a world-wide mul...
متن کاملMultiple-Network Classification of Childhood Autism Using Functional Connectivity Dynamics
Characterization of disease using stationary resting-state functional connectivity (FC) has provided important hallmarks of abnormal brain activation in many domains. Recent studies of resting-state functional magnetic resonance imaging (fMRI), however, suggest there is a considerable amount of additional knowledge to be gained by investigating the variability in FC over the course of a scan. W...
متن کاملPrediction of Autism Treatment Response from Baseline fMRI using Random Forests and Tree Bagging
Treating children with autism spectrum disorders (ASD) with behavioral interventions, such as Pivotal Response Treatment (PRT), has shown promise in recent studies. However, deciding which therapy is best for a given patient is largely by trial and error, and choosing an ineffective intervention results in loss of valuable treatment time. We propose predicting patient response to PRT from basel...
متن کاملConnectivity in Random Forests and Credit Networks
Recent work has highlighted credit networks as an effective mechanism for modeling trust in a network: agents issue their own currency and trust each other for a certain amount of each other’s currency, allowing two nodes to transact if there is a chain of sufficient residual trust between them. Under a natural model of repeated transactions, the probability that two agents can successfully tra...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Neural Computing and Applications
سال: 2019
ISSN: 0941-0643,1433-3058
DOI: 10.1007/s00521-019-04346-y