Gastroenterology

Latest AI and machine learning research in gastroenterology for healthcare professionals.

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Supervised Machine Learning Models for Predicting Sepsis-Associated Liver Injury in Patients With Sepsis: Development and Validation Study Based on a Multicenter Cohort Study.

BACKGROUND: Sepsis-associated liver injury (SALI) is a severe complication of sepsis that contributes to increased mortality and morbidity. Early identification of SALI can improve patient outcomes; however, sepsis heterogeneity makes timely diagnosis challenging. Traditional diagnostic tools are often limited, and machine learning techniques offer promising solutions for predicting adverse outcom...

May 26 2025 40418571

Holistic White-light Polyp Classification via Alignment-free Dense Distillation of Auxiliary Optical Chromoendoscopy

White Light Imaging (WLI) and Narrow Band Imaging (NBI) are the two main colonoscopic modalities for polyp classification. While NBI, as optical chromoendoscopy, offers valuable vascular details, WLI remains the most common and often the only available modality in resource-limited settings. However, WLI-based methods typically underperform, limiting their clinical applicability. Existing approac...

[Integrated diagnosis and treatment of peritoneal metastasis in gastric cancer].

The high incidence and mortality rates of gastric cancer pose a significant burden on human health and public health systems. Peritoneal metastasis is...

May 25 2025 40404362
[Clinical value of medical imaging artificial intelligence in the diagnosis and treatment of peritoneal metastasis in gastrointestinal cancers].

Peritoneal metastasis is a key factor in the poor prognosis of advanced gastrointestinal cancer patients. Traditional radiological diagnostic faces ch...

May 25 2025 40404364
Differentiability of voice disorders through explainable AI.

The voice can be affected by various types of pathology. The phoniatric medical examination is the acoustic analysis, which evaluates the characterist...

May 25 2025 40415073
A Foundation Model Framework for Multi-View MRI Classification of Extramural Vascular Invasion and Mesorectal Fascia Invasion in Rectal Cancer

Background: Accurate MRI-based identification of extramural vascular invasion (EVI) and mesorectal fascia invasion (MFI) is pivotal for risk-stratif...

Evaluation of Few-Shot Learning Methods for Kidney Stone Type Recognition in Ureteroscopy

Determining the type of kidney stones is crucial for prescribing appropriate treatments to prevent recurrence. Currently, various approaches exist t...

A Data-Driven Approach to Assessing Hepatitis B Mother-to-Child Transmission Risk Prediction Model: Machine Learning Perspective.

BACKGROUND: Hepatitis B virus (HBV) can be transmitted from mother to child either through transplacental infection or via blood-to-blood contact duri...

May 23 2025 40409750
Background Matters: A Cross-view Bidirectional Modeling Framework for Semi-supervised Medical Image Segmentation

Semi-supervised medical image segmentation (SSMIS) leverages unlabeled data to reduce reliance on manually annotated images. However, current SOTA a...

Radiomics-based machine learning model for diagnosing internal abdominal hernias: a retrospective study.

Intraperitoneal hernia is an acute abdominal disease, with complex imaging features and variable clinical manifestations that challenge surgeons and e...

May 22 2025 40404730
EndoVLA: Dual-Phase Vision-Language-Action Model for Autonomous Tracking in Endoscopy

In endoscopic procedures, autonomous tracking of abnormal regions and following circumferential cutting markers can significantly reduce the cogniti...

Machine learning in colorectal polyp surveillance: A paradigm shift in post-endoscopic mucosal resection follow-up.

Colorectal cancer remains a major health concern, with colorectal polyps as key precursors. Endoscopic mucosal resection (EMR) is a common treatment, ...

May 21 2025 40497087
Application of deep learning models in the pathological classification and staging of esophageal cancer: A focus on Wave-Vision Transformer.

BACKGROUND: Esophageal cancer is the sixth most common cancer worldwide, with a high mortality rate. Early prognosis of esophageal abnormalities can i...

May 21 2025 40497091
Characterization of subepithelial tumors of upper gastrointestinal tract by endoscopic ultrasound.

In this article we comment on the paper by Xu describing retrospective data on endoscopic treatment outcome of esophageal gastrointestinal stromal tu...

May 21 2025 40497095
Serum calcium-based interpretable machine learning model for predicting anastomotic leakage after rectal cancer resection: A multi-center study.

BACKGROUND: Despite the promising prospects of utilizing artificial intelligence and machine learning (ML) for comprehensive disease analysis, few mod...

May 21 2025 40497096
FasNet: a hybrid deep learning model with attention mechanisms and uncertainty estimation for liver tumor segmentation on LiTS17.

Liver cancer, especially hepatocellular carcinoma (HCC), remains one of the most fatal cancers globally, emphasizing the critical need for accurate tu...

May 21 2025 40399406
Pathobiological Dictionary Defining Pathomics and Texture Features: Addressing Understandable AI Issues in Personalized Liver Cancer; Dictionary Version LCP1.0

Artificial intelligence (AI) holds strong potential for medical diagnostics, yet its clinical adoption is limited by a lack of interpretability and ...

AI-Driven Multiscale Study on the Mechanism of Polygonati Rhizoma in Regulating Immune Function in STAD.

Polygonati Rhizoma, a traditional Chinese medicine, has demonstrated immunomodulatory and anticancer properties, yet its precise mechanisms in stomach...

May 20 2025 40415801
Machine Learning on Toxicogenomic Data Reveals a Strong Association Between the Induction of Drug-Metabolizing Enzymes and Centrilobular Hepatocyte Hypertrophy in Rats.

Centrilobular hepatocyte hypertrophy is frequently observed in animal studies for chemical safety assessment. Although its toxicological significance ...

May 20 2025 40430025
A Digital Score Based on Circulating-Tumor-Cells-Derived mRNA Quantification and Machine Learning for Early Colorectal Cancer Detection.

Circulating tumor cells (CTCs) serve as valuable biomarkers in tumor circulation, carrying essential primary tumor information. The purification of CT...

May 20 2025 40335073
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