Advances in multimodal data fusion in neuroimaging: overview, challenges, and novel orientation
Multimodal fusion in neuroimaging combines data from multiple imaging modalities to
overcome the fundamental limitations of individual modalities. Neuroimaging fusion can …
overcome the fundamental limitations of individual modalities. Neuroimaging fusion can …
An overview of artificial intelligence techniques for diagnosis of Schizophrenia based on magnetic resonance imaging modalities: Methods, challenges, and future …
Schizophrenia (SZ) is a mental disorder that typically emerges in late adolescence or early
adulthood. It reduces the life expectancy of patients by 15 years. Abnormal behavior …
adulthood. It reduces the life expectancy of patients by 15 years. Abnormal behavior …
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 …
[HTML][HTML] Multi-modality approaches for medical support systems: A systematic review of the last decade
Healthcare traditionally relies on single-modality approaches, which limit the information
available for medical decisions. However, advancements in technology and the availability …
available for medical decisions. However, advancements in technology and the availability …
Data sharing and privacy issues in neuroimaging research: Opportunities, obstacles, challenges, and monsters under the bed
Collaborative networks and data sharing initiatives are broadening the opportunities for the
advancement of science. These initiatives offer greater transparency in science, with the …
advancement of science. These initiatives offer greater transparency in science, with the …
[HTML][HTML] Multimodal neuromarkers in schizophrenia via cognition-guided MRI fusion
Cognitive impairment is a feature of many psychiatric diseases, including schizophrenia.
Here we aim to identify multimodal biomarkers for quantifying and predicting cognitive …
Here we aim to identify multimodal biomarkers for quantifying and predicting cognitive …
Neuroimaging and multiomics reveal cross-scale circuit abnormalities in schizophrenia
Schizophrenia (SCZ) is a highly heterogeneous disorder with diverse clinical manifestations
and macro-and microscale biological variations, usually observed at dissociable levels …
and macro-and microscale biological variations, usually observed at dissociable levels …
[HTML][HTML] Altered dynamic functional connectivity of cuneus in schizophrenia patients: a resting-state fMRI study
Objective: Schizophrenia (SZ) is a functional mental condition that has a significant impact
on patients' social lives. As a result, accurate diagnosis of SZ has attracted researchers' …
on patients' social lives. As a result, accurate diagnosis of SZ has attracted researchers' …
[HTML][HTML] Cognitive impairment in schizophrenia: relationships with cortical thickness in fronto-temporal regions, and dissociability from symptom severity
Cognitive impairments are a core and persistent characteristic of schizophrenia with
implications for daily functioning. These show only limited response to antipsychotic …
implications for daily functioning. These show only limited response to antipsychotic …
Deep multimodal predictome for studying mental disorders
Characterizing neuropsychiatric disorders is challenging due to heterogeneity in the
population. We propose combining structural and functional neuroimaging and genomic …
population. We propose combining structural and functional neuroimaging and genomic …