University of Michigan Udall Researchers’ Article Named One of the Top-50 Neuroscience Papers for 2018 (by downloads)

Congratulations to University of Michigan’s Udall researchers whose article, Model-based and Model-free Machine Learning Techniques for Diagnostic Prediction and Classification of Clinical Outcomes in Parkinson’s Disease, received 2,663 article views in 2018, placing it as one of the top 100 read neuroscience papers for Scientific Reports in 2018.

Scientific Reports published more than 1, 627 neuroscience papers in 2018, and so a position in the top 100 most highly read articles is an extraordinary achievement. Access to these highly viewed articles within this category can be found on Scientific Reports Top 100 in neuroscience page.

Read the full article below:

Gao C, Sun H, Wang T, Tang M, Bohnen NI, Müller MLTM, Herman, T, Giladi, N. Kalinin, A, Spino, C, Dauer, W, Hausdorff, JM, Dinov, ID. (2018) Model-based and Model-free Machine Learning Techniques for Diagnostic Prediction and Classification of Clinical Outcomes in Parkinson’s Disease, Scientific Reports, 8(1):7129. doi: 10.1038/s41598-018-24783-4 2018.