Researchers trained a machine learning algorithm to distinguish the brain patterns of patients with functional neurological disorder (FND) from those of healthy individuals and participants with psychiatric disorders. What is Functional Neurological Disorder
In this study, we investigated whether structural brain MRI has potential to be a clinically useful tool for diagnosing FND. Individuals with FND, a common, costly and potentially disabling condition at the intersection of neurology and psychiatry, can experience physical symptoms such as abnormal movements, limb weakness and/or convulsions.
Early Life Trauma Linked to Functional Neurological Disorder
Early trauma such as childhood abuse in life may be a contributing factor for the development of the functional neurological disorder (FND), reports a new study.‘#Machinelearning algorithms are now capable of classifying functional #neurologicaldisorder (FND) by analyzing distinct brain patterns. This advanced classification technology offers a promising approach to differentiating #FND from other #neurological and #psychiatric conditions.’
We trained a machine learning algorithm to learn what the brains of patients with FND look like compared to healthy subjects or participants with psychiatric disorders (e.g., mood and anxiety conditions) that do not have FND, and then tested whether the algorithm could use this information to predict whether someone had FND.
Our findings point out the importance of both brain structure and function in the biological basis of FND.
Furthermore, the algorithm showed proof-of-concept potential in distinguishing individuals with FND, which is a first step in investigating the possibility to use structural brain MRI to assist in the diagnosis of FND.
Brain Structure Changes in Functional Neurological Disorder
The structural relationships between the brain’s network and the physical and mental health of patients with Functional neurological disorder (FND) has been discovered.We sought to investigate whether supervised machine learning, trained on structural brain MRI features, could be used to predict whether individuals had a diagnosis of functional neurological disorder (FND).This question was motivated by a lack of clinical translatability from past studies investigating grey matter differences in FND, because they have for the most part relied on univariate, group-level analyses, and have reported heterogeneous findings.Advertisement Do You Know Your Brain? Test […]
How Machine Learning Transforms Functional Neurological Disorder Classification?
