The normative modeling framework for computational psychiatry
Normative modeling is an emerging and innovative framework for mapping individual
differences at the level of a single subject or observation in relation to a reference model. It …
differences at the level of a single subject or observation in relation to a reference model. It …
Site effects how-to and when: An overview of retrospective techniques to accommodate site effects in multi-site neuroimaging analyses
Site differences, or systematic differences in feature distributions across multiple data-
acquisition sites, are a known source of heterogeneity that may adversely affect large-scale …
acquisition sites, are a known source of heterogeneity that may adversely affect large-scale …
Evidence for embracing normative modeling
In this work, we expand the normative model repository introduced in Rutherford et al.,
2022a to include normative models charting lifespan trajectories of structural surface area …
2022a to include normative models charting lifespan trajectories of structural surface area …
Charting brain growth and aging at high spatial precision
Defining reference models for population variation, and the ability to study individual
deviations is essential for understanding inter-individual variability and its relation to the …
deviations is essential for understanding inter-individual variability and its relation to the …
[HTML][HTML] Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation
R Ge, Y Yu, YX Qi, Y Fan, S Chen, C Gao… - The Lancet Digital …, 2024 - thelancet.com
The value of normative models in research and clinical practice relies on their robustness
and a systematic comparison of different modelling algorithms and parameters; however …
and a systematic comparison of different modelling algorithms and parameters; however …
Closing the life-cycle of normative modeling using federated hierarchical Bayesian regression
Clinical neuroimaging data availability has grown substantially in the last decade, providing
the potential for studying heterogeneity in clinical cohorts on a previously unprecedented …
the potential for studying heterogeneity in clinical cohorts on a previously unprecedented …
A hybrid extreme learning machine and deep belief network framework for sludge bulking monitoring in a dynamic wastewater treatment process
In biological wastewater treatment plants (WWTPs), sludge thickening is a common problem
with major economic and environmental effects. Monitoring the sludge volume index (SVI) is …
with major economic and environmental effects. Monitoring the sludge volume index (SVI) is …
Normative modeling of neuroimaging data using generalized additive models of location scale and shape
Normative modeling aims to quantify the degree to which an individual's brain deviates from
a reference sample with respect to one or more variables, which can be used as a potential …
a reference sample with respect to one or more variables, which can be used as a potential …
[HTML][HTML] Normative models for neuroimaging markers: Impact of model selection, sample size and evaluation criteria
Modelling population reference curves or normative modelling is increasingly used with the
advent of large neuroimaging studies. In this paper we assess the performance of fitting …
advent of large neuroimaging studies. In this paper we assess the performance of fitting …
[HTML][HTML] Deviations from normative brain white and gray matter structure are associated with psychopathology in youth
Combining imaging modalities and metrics that are sensitive to various aspects of brain
structure and maturation may help identify individuals that show deviations in relation to …
structure and maturation may help identify individuals that show deviations in relation to …