zenodorestricted
Dataset for "Sulcal Morphometry Predicts Mild Cognitive Impairment Conversion to Alzheimer's Disease"
<p>The dataset contains the numerical data described and analyzed in the paper "Sulcal Morphometry Predicts Mild Cognitive Impairment Conversion to Alzheimer’s Disease", Sighinolfi et al., J Alzheimers Dis, 2024, doi: 10.3233/JAD-231192.</p> <p>It consists of the measures, performed using the Morphologist software, of the morphological properties of brain sulci in 87 subjects, as described in the paper.</p> <p>If interested in the data, please contact the Corresponding Author: <br>Prof. Caterina Tonon<br>caterina.tonon@unibo.it</p>
ShareScore
16/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 8
- Reuse readiness
- 0
- Engagement
- 0