Gastroenterology

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

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Polarisation Sensitive Optical Coherence Tomography Image Characteristics for Gastrointestinal Tumours and Normal Tissues at Surgical Margins in Dogs.

The treatment of choice for canine alimentary tract neoplasms is surgical excision, but it can somet...

Demarcating the Development of Cirrhosis and Its Complications via Plasma Proteomic Features in an Asymptomatic Population.

The early detection of liver cirrhosis and its complications is a conundrum in clinical practice. We...

Study on the quantitative analysis of Tilianin based on Raman spectroscopy combined with deep learning.

Tilianin is a commonly used pharmaceutical ingredient with various biological activities such as ant...

Three-dimensional multimodal imaging for predicting early recurrence of hepatocellular carcinoma after surgical resection.

BACKGROUND: High tumor recurrence after surgery remains a significant challenge in managing hepatoce...

Microbiome multi-omics analysis reveals novel biomarkers and mechanisms linked with CD etiopathology.

BACKGROUND: The gut microbiome plays a key role in the development of inflammatory bowel disease (IB...

The relevance of cardiac and gastric interoception for disordered eating behavior.

BACKGROUND: Gastric interoception (i.e., the perception of gastrointestinal signals such as hunger, ...

Unraveling the power of radiomics: prediction and exploration of lymph node metastasis in stage T1/2 esophageal squamous cell carcinoma.

Accurate assessment of lymph node metastasis (LNM) in T1/2-stage esophageal squamous cell carcinoma ...

Computational theranostics strategy for pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a formidable challenge in modern medicine, characterized ...

Development and validation of machine learning models for distant metastasis of primary hepatic carcinoma: a population-based study.

BACKGROUND: Primary liver cancer is the sixth most common cancer globally and ranks third in cancer-...

Predicting mucosal healing in Crohn's disease: development of a deep-learning model based on intestinal ultrasound images.

OBJECTIVE: Predicting treatment response in Crohn's disease (CD) is essential for making an optimal ...

Artificial intelligence (AI) and CT in abdominal imaging: image reconstruction and beyond.

Computed tomography (CT) is a cornerstone of abdominal imaging, playing a vital role in accurate dia...

Deep Learning Methodology for Quantification of Normal Pancreas Structures.

Histopathologic evaluation plays a crucial role in assessing morphological tissue alterations in dis...

Improving Hepatitis B outcome prediction with ensemble machine learning: A study on predictive models and interpretability.

OBJECTIVE: Hepatitis B virus (HBV) is a significant global health threat, responsible for severe liv...

Signature gene expression model for quantitative evaluation of MASH-like liver injury in mice.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a spectrum of chronic pathologic...

Metastatic hepatic carcinoma: Mechanisms, emerging therapeutics, and future perspectives.

Metastatic hepatic carcinoma (MHC) remains a lethal disease, with a 5-year survival rate of around 1...

Utility of Thin-slice Single-shot T2-weighted MR Imaging with Deep Learning Reconstruction as a Protocol for Evaluating Pancreatic Cystic Lesions.

PURPOSE: To assess the effects of industry-developed deep learning reconstruction with super resolut...

Qualitative evaluation of automatic liver segmentation in computed tomography images for clinical use in radiation therapy.

PURPOSE: Segmentation of target volumes and organs at risk on computed tomography (CT) images consti...

A multimodal fusion system predicting survival benefits of immune checkpoint inhibitors in unresectable hepatocellular carcinoma.

Early identification of unresectable hepatocellular carcinoma (HCC) patients who may benefit from im...

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