This title appears in the Scientific Report :
2022
Please use the identifier:
http://hdl.handle.net/2128/32728 in citations.
Generalizability of connectome-based predictive models
Generalizability of connectome-based predictive models
The development of connectome-based predictive models of behavioral phenotype has more recently opened new perspectives for understanding brain-behavior relationships in basic neuroscience, but also for precision medicine. However, the insight provided by the machine learning models and the further...
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Personal Name(s): | GENON, Sarah (Corresponding author) |
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Contributing Institute: |
Gehirn & Verhalten; INM-7 |
Imprint: |
2022
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Conference: | 20th Brain Connectivity Workshop, Düsseldorf (online event), 2022-06-14 - 2022-06-14 |
Document Type: |
Conference Presentation |
Research Program: |
Multilevel Brain Organization and Variability |
Link: |
Get full text OpenAccess |
Publikationsportal JuSER |
The development of connectome-based predictive models of behavioral phenotype has more recently opened new perspectives for understanding brain-behavior relationships in basic neuroscience, but also for precision medicine. However, the insight provided by the machine learning models and the further deployment of these approaches are conditioned by their generalizability. In our recent work, we tackled this crucial question across several popular datasets in the field. |