Gastroenterology

Artificial intelligence applied to 'omics data in liver disease: towards a personalised approach for diagnosis, prognosis and treatment.

Advancements in omics technologies and artificial intelligence (AI) methodologies are fuelling our progress towards personalised diagnosis, prognosis and treatment strategies in hepatology. This review provides a comprehensive overview of the current landscape of AI methods used for analysis of omics data in liver diseases. We present an overview of the prevalence of different omics levels across ...

Cellular Senescence in Hepatocellular Carcinoma: Immune Microenvironment Insights via Machine Learning and In Vitro Experiments.

Hepatocellular carcinoma (HCC), a leading liver tumor globally, is influenced by diverse risk factors. Cellular senescence, marked by permanent cell cycle arrest, plays a crucial role in cancer biology, but its markers and roles in the HCC immune microenvironment remain unclear. Three machine learning methods, namely k nearest neighbor (KNN), support vector machine (SVM), and random forest (RF), a...

Machine learning-based prediction for incidence of endoscopic retrograde cholangiopancreatography after emergency laparoscopic cholecystectomy: A retrospective, multicenter cohort study.

BACKGROUND: Laparoscopic cholecystectomy is the preferred treatment for symptomatic cholelithiasis and acute cholecystitis, with increasing applicatio...

Multistage deep learning for classification of Helicobacter pylori infection status using endoscopic images.

BACKGROUND: The automated classification of Helicobacter pylori infection status is gaining attention, distinguishing among uninfected (no history of ...

The Role of Industry to Grow Clinical Artificial Intelligence Applications in Gastroenterology and Endoscopy.

The integration of artificial intelligence (AI) in health care has the potential to enhance diagnostics and disease management. In the field of gastro...

A Supervised Explainable Machine Learning Model for Perioperative Neurocognitive Disorder in Liver-Transplantation Patients and External Validation on the Medical Information Mart for Intensive Care IV Database: Retrospective Study.

BACKGROUND: Patients undergoing liver transplantation (LT) are at risk of perioperative neurocognitive dysfunction (PND), which significantly affects ...

Extracting organs of interest from medical images based on convolutional neural network with auxiliary and refined constraints.

Accurately extracting organs from medical images provides radiologist with more comprehensive evidences to clinical diagnose, which offers up a higher...

Development of an interpretable machine learning model based on CT radiomics for the prediction of post acute pancreatitis diabetes mellitus.

This study sought to establish and validate an interpretable CT radiomics-based machine learning model capable of predicting post-acute pancreatitis d...

Development of a LASSO machine learning algorithm-based model for postoperative delirium prediction in hepatectomy patients.

OBJECTIVE: The objective of this study was to develop and validate a clinically applicable nomogram for predicting the risk of delirium following hepa...

Hybrid Control Policy for Artificial Pancreas via Ensemble Deep Reinforcement Learning.

OBJECTIVE: The artificial pancreas (AP) shows promise for closed-loop glucose control in type 1 diabetes mellitus (T1DM). However, designing effective...

Exploring prognosis and therapeutic strategies for HBV-HCC patients based on disulfidptosis-related genes.

BACKGROUND: Hepatocellular carcinoma (HCC) accounts for over 80% of primary liver cancers and is the third leading cause of cancer-related deaths worl...

A comparative evaluation of antibiotic and synbiotic supplementation on production performance and necrotic enteritis severity in broilers during an experimental necrotic enteritis challenge.

The ban on antibiotics in the poultry diet resulted in re-emergence of several infectious diseases including necrotic enteritis (NE). These infectious...

Dynamic spectrum-driven hierarchical learning network for polyp segmentation.

Accurate automatic polyp segmentation in colonoscopy is crucial for the prompt prevention of colorectal cancer. However, the heterogeneous nature of p...

Reducing reading time and assessing disease in capsule endoscopy videos: A deep learning approach.

BACKGROUND: The wireless capsule endoscope (CE) is a valuable diagnostic tool in gastroenterology, offering a safe and minimally invasive visualizatio...

Assessment of different U-Net backbones in segmenting colorectal adenocarcinoma from H&E histopathology.

Adenocarcinoma, the most prevalent type of colorectal cancer, makes up roughly 95 % of all cases and is associated with a notably high mortality rate....

Elevated serum CA 19-9 level mimicking pancreaticobiliary carcinoma from a hepatic abscess: case report and literature review.

Serum levels of the tumor marker CA 19-9 are widely utilized in the diagnosis and monitoring pancreatic and biliary malignancies. However, serum level...

Physalis Calyx seu Fructus relieves chicken intestinal damage to heat via improving the antioxidant ability.

Heat-stress-induced oxidative and inflammatory responses were important factors contributing to chicken intestinal damage. The purpose of this study w...

Integration of Deep Learning and Sub-regional Radiomics Improves the Prediction of Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer Patients.

RATIONALE AND OBJECTIVES: The precise prediction of response to neoadjuvant chemoradiotherapy is crucial for tailoring perioperative treatment in pati...

Toward efficient slide-level grading of liver biopsy via explainable deep learning framework.

In the context of chronic liver diseases, where variability in progression necessitates early and precise diagnosis, this study addresses the limitati...

An Integrated Microfluidic Microwave Array Sensor with Machine Learning for Enrichment and Detection of Mixed Biological Solution.

In this work, an integrated microfluidic microwave array sensor is proposed for the enrichment and detection of mixed biological solution. In individu...