AIMC Topic: Gastrointestinal Tract

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Interpretable deep learning for enhanced multi-class classification of gastrointestinal endoscopic images.

Biomedical physics & engineering express
Gastrointestinal (GI) endoscopy serves as a vital tool for assessing the GI tract and diagnosing related disorders. Recent progress in deep learning has shown significant improvements in identifying anomalies using sophisticated models and data augme...

Integrated multi-omic and symptom clustering reveals lower-gastrointestinal disorders of gut-brain interaction heterogeneity.

Gut microbes
Rome IV disorders of gut-brain interaction (DGBI) subtypes are known to be unstable and demonstrate high rates of non-treatment response, likely indicating patient heterogeneity. Cluster analysis, a type of unsupervised machine learning, can identify...

A review on computer-aided diagnostic system to classify the disorders of the gastrointestinal tract.

European journal of medical research
Various diseases, such as colon cancer, gastric cancer, celiac, and bleeding, pose a significant risk to the gastrointestinal (GI) tract, which serves as a fundamental component of the human body. It is less invasive to observe the inner part for dis...

Deep multi-task learning framework for gastrointestinal lesion-aided diagnosis and severity estimation.

Scientific reports
Accurate diagnosis and severity estimation of gastrointestinal tract (GT) lesions are crucial for patient care and effective treatment plan decisions. Traditional methods for diagnosing lesions face challenges in accurately estimating severity due to...

4-Hydroxyboesenbergin B of Alpinia japonica protected gastrointestinal tract by inhibiting vancomycin-resistant enterococcus and balancing intestinal microbiota.

Journal of ethnopharmacology
ETHNOPHARMACOLOGICAL RELEVANCE: Alpinia japonica, a traditional herb utilized in Miao medicine in southwestern China, has been employed to alleviate symptoms such as stomachache, diarrhea, and abdominal pain, some of these symptoms may be associated ...

S2P-Matching: Self-Supervised Patch-Based Matching Using Transformer for Capsule Endoscopic Images Stitching.

IEEE transactions on bio-medical engineering
The Magnetically Controlled Capsule Endoscopy (MCCE) has a limited shooting range, resulting in capturing numerous fragmented images and an inability to precisely locate and examine the region of interest (ROI) as traditional endoscopy can. Addressin...

Artificial Intelligence in Gastrointestinal Imaging: Advances and Applications.

Radiologic clinics of North America
While artificial intelligence (AI) has shown considerable progress in many areas of medical imaging, applications in abdominal imaging, particularly for the gastrointestinal (GI) system, have notably lagged behind advancements in other body regions. ...

Identification of Key Genes in Fetal Gut Development at Single-Cell Level by Exploiting Machine Learning Techniques.

Proteomics
The study of fetal gut development is critical due to its substantial influence on immediate neonatal and long-term adult health. Current research largely focuses on microbiome colonization, gut immunity, and barrier function, alongside the impact of...

Towards reliable data: Validation of a machine learning-based approach for microplastics analysis in marine organisms using Nile red staining.

Marine pollution bulletin
Microplastic (MP) research faces challenges due to costly, time-consuming, and error-prone analysis techniques. Additionally, the variability in data quality across studies limits their comparability. This study addresses the critical need for reliab...