ArticleBrain sciences2020
Logistic Regression Algorithm Differentiates Gulf War Illness (GWI) Functional Magnetic Resonance Imaging (fMRI) Data from a Sedentary Control.
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 5 papers.
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Who cites it
5 citing papers in PubMed.
- Longitudinal Assessment of Ocular Biomarkers in Individuals With Gulf War Illness Symptoms.Military medicine · 2025Article
- Mapping the brain's fatigue network: a transdiagnostic systematic review and meta-analysis on functional correlates of mental fatigue.Brain communications · 2025Review
- Advancing the Role of Neuroimmunity and Genetic Susceptibility in Gulf War Illness.Brain sciences · 2022Article
- Article
- Machine Learning Detects Pattern of Differences in Functional Magnetic Resonance Imaging (fMRI) Data between Chronic Fatigue Syndrome (CFS) and Gulf War Illness (GWI).Brain sciences · 2020Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Gulf War Illness (GWI) is a debilitating condition characterized by dysfunction of cognition, pain, fatigue, sleep, and diverse somatic symptoms with no known underlying pathology. As such, uncovering objective biomarkers such as differential regions of activity within a Functional Magnetic Resonance Imaging (fMRI) scan is important to enhance validity of the criteria for diagnosis. Symptoms are exacerbated by mild activity, and exertional exhaustion is a key complaint amongst sufferers. We modeled this exertional exhaustion by having GWI (
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