ArticleBrain sciences2020
Quantitative Identification of Functional Connectivity Disturbances in Neuropsychiatric Lupus Based on Resting-State fMRI: A Robust Machine Learning Approach.
Article in Brain sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 3 of them syntheses that pooled it.
What it found
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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.
The trial behind it
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
14 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Diagnostic Performance of Machine Learning for Systemic Lupus Erythematosus: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Artificial Intelligence-based detection of neuropsychiatric lupus: an exploratory meta-analysis of neuroimaging and multimodal biomarker models.Clinical and experimental medicine · 2026Pooled it
- Machine Learning for Diagnosis of Systemic Lupus Erythematosus: A Systematic Review and Meta-Analysis.Computational intelligence and neuroscience · 2022Pooled it
- [Classification of systemic lupus erythematosus resting-state functional magnetic resonance imaging data based on the end-to-end model].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026Article
- Machine Learning for MRI Classification of Systemic Lupus Erythematous Patients with and without Neuropsychiatric Events.Journal of imaging informatics in medicine · 2026Article
- Current imaging applications, radiomics, and machine learning modalities of CNS demyelinating disorders and its mimickers.Journal of neurology · 2025Review
- Abnormal brain functional networks in systemic lupus erythematosus: a graph theory, network-based statistic and machine learning study.Brain communications · 2025Article
- Functional connectivity-hemodynamic (un)coupling changes in chronic mild brain injury are associated with mental health and neurocognitive indices: a resting state fMRI study.Neuroradiology · 2024Article
- Systemic lupus in the era of machine learning medicine.Lupus science & medicine · 2024Review
- Altered hippocampal connectivity dynamics predicts memory performance in neuropsychiatric lupus: a resting-state fMRI study using cross-recurrence quantification analysis.Lupus science & medicine · 2023Article
- Personalized Risk Analysis to Improve the Psychological Resilience of Women Undergoing Treatment for Breast Cancer: Development of a Machine Learning-Driven Clinical Decision Support Tool.Journal of medical Internet research · 2023Article
- Chronic Mild Traumatic Brain Injury: Aberrant Static and Dynamic Connectomic Features Identified Through Machine Learning Model Fusion.Neuroinformatics · 2023Article
- An introduction to machine learning and analysis of its use in rheumatic diseases.Nature reviews. Rheumatology · 2021Review
- Latest Advances in Human Brain Dynamics.Brain sciences · 2021Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Neuropsychiatric systemic lupus erythematosus (NPSLE) is an autoimmune entity comprised of heterogenous syndromes affecting both the peripheral and central nervous system. Research on the pathophysiological substrate of NPSLE manifestations, including functional neuroimaging studies, is extremely limited. The present study examined person-specific patterns of whole-brain functional connectivity in NPSLE patients (
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Registered trials
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.