The challenges and prospects of brain-based prediction of behaviour
Relating individual brain patterns to behaviour is fundamental in system neuroscience.
Recently, the predictive modelling approach has become increasingly popular, largely due …
Recently, the predictive modelling approach has become increasingly popular, largely due …
Functional brain networks are associated with both sex and gender in children
Sex and gender are associated with human behavior throughout the life span and across
health and disease, but whether they are associated with similar or distinct neural …
health and disease, but whether they are associated with similar or distinct neural …
MRI economics: Balancing sample size and scan duration in brain wide association studies
A pervasive dilemma in neuroimaging is whether to prioritize sample size or scan time given
fixed resources. Here, we systematically investigate this trade-off in the context of brain-wide …
fixed resources. Here, we systematically investigate this trade-off in the context of brain-wide …
Multilayer meta-matching: translating phenotypic prediction models from multiple datasets to small data
Resting-state functional connectivity (RSFC) is widely used to predict phenotypic traits in
individuals. Large sample sizes can significantly improve prediction accuracies. However …
individuals. Large sample sizes can significantly improve prediction accuracies. However …
[HTML][HTML] Brain-based predictions of psychiatric illness–linked behaviors across the sexes
Background Individual differences in functional brain connectivity can be used to predict
both the presence of psychiatric illness and variability in associated behaviors. However …
both the presence of psychiatric illness and variability in associated behaviors. However …
Generalizable and replicable brain-based predictions of cognitive functioning across common psychiatric illness
A primary aim of computational psychiatry is to establish predictive models linking individual
differences in brain functioning with symptoms. In particular, cognitive impairments are …
differences in brain functioning with symptoms. In particular, cognitive impairments are …
A multi-strategy hybrid machine learning model for predicting glass-formation ability of metallic glasses based on imbalanced datasets
X Liu, Z Long, W Zhang, L Yang, Z Li - Journal of Non-Crystalline Solids, 2023 - Elsevier
The glass-forming ability (GFA) is essential to developing and broadly applying metallic
glasses. However, existing research rarely considers the imbalance of GFA data, which …
glasses. However, existing research rarely considers the imbalance of GFA data, which …
[HTML][HTML] Advanced feature engineering in microgrid PV forecasting: A fast computing and data-driven hybrid modeling framework
MA Habib, MJ Hossain - Renewable Energy, 2024 - Elsevier
This study introduces an innovative framework designed to forecast the fluctuating short-
term generation of photovoltaic (PV) energy in isolated microgrids. The framework relies …
term generation of photovoltaic (PV) energy in isolated microgrids. The framework relies …
Network-level enrichment provides a framework for biological interpretation of machine learning results
Abstract Machine learning algorithms are increasingly being utilized to identify brain
connectivity biomarkers linked to behavioral and clinical outcomes. However, research often …
connectivity biomarkers linked to behavioral and clinical outcomes. However, research often …
Reliable and generalizable brain-based predictions of cognitive functioning across common psychiatric illness
A primary aim of precision psychiatry is the establishment of predictive models linking
individual differences in brain functioning with clinical symptoms. In particular, cognitive …
individual differences in brain functioning with clinical symptoms. In particular, cognitive …