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
|
|---|---|
| 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% |