Using Deep Learning and Resting-State fMRI to Classify Chronic Pain Conditions

Show simple item record Novaes Santana, Alex Cifre, Ignacio Novaes de Santana, Charles Montoya, Pedro 2020-03-10T12:25:16Z 2020-03-10T12:25:16Z
dc.description.abstract [eng] Chronic pain is known as a complex disease due to its comorbidities with other symptoms and the lack of effective treatments. As a consequence, chronic pain seems to be under-diagnosed in more than 75% of patients. At the same time, the advance in brain imaging, the popularization of machine learning techniques and the development of new diagnostic tools based on these technologies have shown that these tools could be an option in supporting decision-making of healthcare professionals. In this study, we computed functional brain connectivity using resting-state fMRI data from one hundred and fifty participants to assess the performance of different machine learning models, including deep learning (DL) neural networks in classifying chronic pain patients and pain-free controls. The best result was obtained by training a convolutional neural network fed with data preprocessed using the MSDL probabilistic atlas and using the dynamic time warping (DTW) as connectivity measure. DL models had a better performance compared to other less costly models such as support vector machine (SVM) and RFC, with balanced accuracy ranged from 69 to 86%, while the area under the curve (ROC) ranged from 0.84 to 0.93. Also, DTW overperformed correlation as connectivity measure. These findings support the notion that resting-state fMRI data could be used as a potential biomarker of chronic pain conditions.
dc.format application/pdf
dc.relation.ispartof Frontiers In Neuroscience, 2019, p. 1-13
dc.rights , 2019
dc.subject.classification 616.8 - Neurologia. Neuropatologia. Sistema nerviós
dc.subject.other 616.8 - Neurology. Neuropathology. Nervous system
dc.title Using Deep Learning and Resting-State fMRI to Classify Chronic Pain Conditions
dc.type info:eu-repo/semantics/article 2020-03-10T12:25:16Z
dc.rights.accessRights info:eu-repo/semantics/openAccess

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