ReviewBiological psychiatry2024
Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning.
Review in Biological psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 3 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
20 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Network localization of regional intrinsic neural activity alterations in migraine and their neurochemical correlates.Frontiers in neurology · 2026Pooled it
- Artificial intelligence support for diagnosis of neurodevelopmental disorders during childhood: an umbrella review.Frontiers in psychiatry · 2026Pooled it
- Neuroimaging Insights into the Public Health Burden of Neuropsychiatric Disorders: A Systematic Review of Electroencephalography-Based Cognitive Biomarkers.Medicina (Kaunas, Lithuania) · 2025Pooled it
- Brain Connectivity and Machine Learning Approaches to assess the underlying neurobiology and prediction accuracy of anorexia nervosa: A replication study.Psychiatry research. Neuroimaging · 2026Article
- Reinforcement learning-driven adaptive game therapy for cognitive impairment patients with improved vision transformer based detection model.BMC psychology · 2026Article
- Decomposing neuroanatomical heterogeneity in depression: insights from an ENIGMA major depressive disorder working group study in 5146 individuals.Translational psychiatry · 2026Article
- Coupled cross-sectional and longitudinal non-negative matrix factorization reveals dominant brain aging trajectories in 48,949 individuals.Nature communications · 2026Article
- Multi-organ AI endophenotypes chart the heterogeneity of brain, eye and heart pan-disease.Nature. Mental health · 2026Article
- Network localization of gray matter alterations in chronic smokers using the normative functional connectome.Frontiers in public health · 2026Article
- How gut microbiota contribute to neuropsychiatric disorders: evidence from neuroimaging studies.Frontiers in microbiology · 2026Review
- Neurodevelopmental disorders in children: the role of MRI in early detection and intervention planning.Frontiers in neuroscience · 2026Review
- Artificial Intelligence Networks Combining Histopathology and Machine Learning Can Extract Axon Pathology in Autism Spectrum Disorder.Autism research : official journal of the International Society for Autism Research · 2025Article
- Generating MRI-Derived CSF Proxy-Markers to Predict and Visualize Alzheimer's Disease Progression.Human brain mapping · 2025Article
- Cortical thickness subtypes in cognitively unimpaired individuals: Differential network and transcriptomic vulnerability to cortical thinning.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Dissecting real-world memory clinical cohort heterogeneity: analysis of neuroanatomical subtypes using HYDRA.Alzheimer's research & therapy · 2025Article
- Practical AI application in psychiatry: historical review and future directions.Molecular psychiatry · 2025Review
- Towards a multi-organ, multi-omics medical digital twin.Nature biomedical engineering · 2025Article
- Merging multimodal digital biomarkers into "Digital Neuro Fingerprints" for precision neurology in dementias: the promise of the right treatment for the right patient at the right time in the age of AI.Frontiers in digital health · 2025Article
- Perinatal Hypoxia and Immune System Activation in Schizophrenia Pathogenesis: Critical Considerations During COVID-19 Pandemic.Physiological research · 2024Review
- Task-based functional neural correlates of social cognition across autism and schizophrenia spectrum disorders.Molecular autism · 2024Article
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7 authors.
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Abstract
Machine learning has been increasingly used to obtain individualized neuroimaging signatures for disease diagnosis, prognosis, and response to treatment in neuropsychiatric and neurodegenerative disorders. Therefore, it has contributed to a better understanding of disease heterogeneity by identifying disease subtypes with different brain phenotypic measures. In this review, we first present a systematic literature overview of studies using machine learning and multimodal magnetic resonance imaging to unravel disease heterogeneity in various neuropsychiatric and neurodegenerative disorders, including Alzheimer's disease, schizophrenia, major depressive disorder, autism spectrum disorder, and multiple sclerosis, as well as their potential in a transdiagnostic framework, where neuroanatomical and neurobiological commonalities were assessed across diagnostic boundaries. Subsequently, we summarize relevant machine learning methodologies and their clinical interpretability. We discuss the potential clinical implications of the current findings and envision future research avenues. Finally, we discuss an emerging paradigm called dimensional neuroimaging endophenotypes. Dimensional neuroimaging endophenotypes dissects the neurobiological heterogeneity of neuropsychiatric and neurodegenerative disorders into low-dimensional yet informative, quantitative brain phenotypic representations, serving as robust intermediate phenotypes (i.e., endophenotypes), presumably reflecting the interplay of underlying genetic, lifestyle, and environmental processes associated with disease etiology.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.