Last Posted: Sep 18, 2019
- Machine-learning identifies Parkinson's disease patients based on resting-state between-network functional connectivity.
Rubbert Christian et al. The British journal of radiology 2019 Sep 92(1101) 20180886
- Using gait analysis' parameters to classify Parkinsonism: A data mining approach.
Ricciardi Carlo et al. Computer methods and programs in biomedicine 2019 Aug 180105033
- Penetrance of Parkinson’s disease in LRRK2 p.G2019S carriers is modified by a polygenic risk score
H Iwaki et al, BioRXIV, August 20, 2019
- The genetics of Parkinson disease.
Deng Hao et al. Ageing research reviews 2018 Mar 4272-85
- Convolutional neural network-based segmentation can help in assessing the substantia nigra in neuromelanin MRI.
Le Berre Alice et al. Neuroradiology 2019 Aug
- Towards On-Demand Virtual Physical Therapist: Machine Learning-Based Patient Action Understanding, Assessment and Task Recommendation.
Wei Wenchuan et al. IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society 2019 Aug
- Artificial intelligence for assisting diagnostics and assessment of Parkinson's disease-A review.
Belic Minja et al. Clinical neurology and neurosurgery 2019 Jul 184105442
- [ 123 I]Metaiodobenzylguanidine (MIBG) Cardiac Scintigraphy and Automated Classification Techniques in Parkinsonian Disorders.
Nuvoli Susanna et al. Molecular imaging and biology : MIB : the official publication of the Academy of Molecular Imaging 2019 Jul
- Harnessing digital technology to predict, diagnose, monitor, and develop treatments for brain disorders.
Stroud Clare et al. NPJ digital medicine 2019 244
- The genetic and clinico-pathological profile of early-onset progressive supranuclear palsy.
Jabbari Edwin et al. Movement disorders : official journal of the Movement Disorder Society 2019 Jul
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