| Literature DB >> 26743974 |
Abstract
Machine learning techniques represent the third-generation of clinical neuroimaging studies where the principal interest is not related to describe anatomical changes of a neurological disorder, but to evaluate if a multivariate approach may use these abnormalities to predict the correct classification of previously unseen clinical cohort. In the next few years, Machine learning will revolutionize clinical practice of Parkinson's disease, but enthusiasm should be turned down before removing some important barriers.Entities:
Keywords: Clinical practice; Computer-based diagnosis; Machine learning; Neuroimaging; Parkinson's disease
Mesh:
Year: 2015 PMID: 26743974 DOI: 10.1016/j.jneumeth.2015.12.005
Source DB: PubMed Journal: J Neurosci Methods ISSN: 0165-0270 Impact factor: 2.390