ArticleIEEE transactions on bio-medical engineering2022
Robust Regression and Optimal Transport Methods to Predict Gastrointestinal Disease Etiology From High Resolution EGG and Symptom Severity.
Article in IEEE transactions on bio-medical engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 14 citations in OpenAlex.
- Review
- An EfficientNet-based hierarchical dual-encoder framework for multi-scale gastrointestinal disease detection.Scientific reports · 2026Article
- Entropy as a Tool for Quantifying Biomedical Signals: Gaps and Opportunities in Clinical Methodological Approaches-A Scoping Review.Biomedical engineering and computational biology · 2026Review
- Multimodal subspace identification for modeling discrete-continuous spiking and field potential population activity.Journal of neural engineering · 2024Article
- Emerging wearable technologies for multisystem monitoring and treatment of Parkinson's disease: a narrative review.Frontiers in network physiology · 2024Review
- Unsupervised learning of stationary and switching dynamical system models from Poisson observations.Journal of neural engineering · 2023Article
- Endoscopic mucosal electrodes: New directions for recording and regulating gastric myoelectric activity.Frontiers in surgery · 2022Review
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3 authors at 3 institutions in 1 country.
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Abstract
objectiveGastric functional and motility disorders are highly prevalent, with gastroparesis (GP) and functional dyspepsia (FD), affecting 1.5-3% and 10% of the population, respectively. Multiple disease etiologies with overlapping symptoms, such as antral hypomotility, pylorospasm, autonomic dysfunction, and gastric myoelectric dysfunction underlie GP and FD. There is an unmet need to differentiate these etiologies non-invasively to tailor treatment strategies and predict treatment response.
methodsWe performed cutaneous high-resolution electrogastrogram (HR-EGG) recordings on 32 human subjects (controls, GP, and FD) and computed gastric slow wave propagation patterns. We implemented robust regression and clustering methods to identify one group of patients with symptoms well explained by spatial slow wave features and another with symptom severity significantly exceeding predictions from spatial slow wave features. Five patients were re-assessed with validated symptom questionnaires after pyloric and prokinetic interventions.
resultsA group of seven patients was identified whose spatial slow wave features lie within the same range as control subjects but whose symptom severity significantly exceeded what is predicted from spatial slow wave features. We hypothesize that gastric myoelectric dysfunction is not a prominent disease etiology in this group. A highly accurate regression holds in the other group of patients (r=0.8). Of the patients with repeat questionnaires, patients with symptom severity exceeding the regression line reported symptom improvement, whereas patients with symptoms in close proximity to the regression line experienced no improvement.
conclusionThese findings suggest that patients with symptom severity significantly exceeding the robust regression line have symptoms that cannot be explained by gastric myoelectric dysfunction alone, and vice versa. SIGNIFICANCE: This methodology may provide clinicians with an opportunity to screen patients to determine when existing interventions will be effective, and on the flipside, when slow wave restoration interventions, such as gastric neuromodulation, may be most effective in improving symptoms and quality of life.
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