The data shown below were compiled from readership statistics for 176 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Mendeley readers
Title |
A Novel Ensemble-Based Machine Learning Algorithm to Predict the Conversion From Mild Cognitive Impairment to Alzheimer's Disease Using Socio-Demographic Characteristics, Clinical Information, and Neuropsychological Measures
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Published in |
Frontiers in Neurology, July 2019
|
DOI | 10.3389/fneur.2019.00756 |
Pubmed ID | |
Authors |
Massimiliano Grassi, Nadine Rouleaux, Daniela Caldirola, David Loewenstein, Koen Schruers, Giampaolo Perna, Michel Dumontier, Alzheimer's Disease Neuroimaging Initiative |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 176 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 21 | 12% |
Student > Ph. D. Student | 20 | 11% |
Researcher | 15 | 9% |
Professor | 10 | 6% |
Student > Doctoral Student | 9 | 5% |
Other | 36 | 20% |
Unknown | 65 | 37% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 24 | 14% |
Neuroscience | 15 | 9% |
Medicine and Dentistry | 14 | 8% |
Psychology | 12 | 7% |
Engineering | 8 | 5% |
Other | 28 | 16% |
Unknown | 75 | 43% |