Gastroenterology

Reconstructing the intestinal microbiota ecological network based on graph neural network and contrastive learning: Predicting key microbiota regulatory targets in Crohn's Disease.

Crohn's disease (CD) is a heterogeneous inflammatory bowel disease in which microbial, metabolic, an...

Machine Learning-Based Identification of Survival-Associated CpG Biomarkers in Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is an exceptionally aggressive cancer with a 5-year survival...

Procedure-specific prediction of surgical difficulty in laparoscopic and robotic right hemicolectomy: Interpretable machine learning models.

BACKGROUND: Laparoscopic (L-RHC) and robotic (R-RHC) right hemicolectomy are standard treatments for...

Trait-based machine learning modeling of soluble carbohydrate content in Trachyspermum ammi exposed to organic and chemical fertilization and salicylic acid.

Accurate assessment of biochemical traits in medicinal plants is essential for supporting environmen...

Brain network correlates of fatigue, depression, and anxiety in patients with Crohn's Disease in different disease states.

BACKGROUND: Symptoms of fatigue, depression or anxiety are frequent in Crohn's Disease (CD) and may ...

Epigenetic editing approaches maturity: AI-driven precision design, delivery innovation, and the road to clinical translation.

Epigenetic editing achieves durable gene silencing through targeted modification of chromatin and DN...

Colorectal Cancer Screening in Hereditary and Familial High-Risk Populations: Best Practices and Future Directions.

Colorectal cancer (CRC) remains a leading cause of cancer-related morbidity and mortality worldwide ...

Evaluating human-AI interaction in optical diagnosis of early colorectal carcinoma through endoscopist responses to simulated artificial intelligence: a multinational online study.

Background Suboptimal human - artificial intelligence (AI) interaction is a potential roadblock for ...

Machine Learning-Based Privacy Preserving via CT/MRI and Organ Metadata Prediction.

Medical imaging plays a significant role in diagnosis and treatment planning, with significant effor...

Digital Pathology-Enabled Artificial Intelligence for Fibrosis Assessment in Metabolic Dysfunction-Associated Steatohepatitis: Needs, Current Progress, and Barriers.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is emerging as the most common chro...

Using artificial intelligence to identify characteristics associated with clinical and economic outcomes in MASH (FOCUS-MASH).

BACKGROUND: Heterogeneity in the disease characteristics of metabolic dysfunction-associated steatoh...

A systematic review on colon cancer classification by convolutional neural networks: Architecture, accuracy, and research directions.

INTRODUCTION: Recent studies indicated the advancement of Convolutional Neural Networks (CNNs) have ...

Dysregulated glucocorticoid-responsive immune genes in peripheral blood mononuclear cells as a shared molecular signature of autism spectrum disorder and irritable bowel syndrome.

BACKGROUND: Autism spectrum disorder (ASD) is frequently accompanied by gastrointestinal (GI) distur...

Physically intelligent capsule robots with embodied memory and logic in the gastrointestinal tract.

Miniaturized medical robots offer a promising solution for minimally invasive measurements and inter...

Comment on "A novel artificial intelligence-based endoscopic ultrasonography diagnostic system for diagnosing the invasion depth of early gastric cancer".

Perioperative corticosteroids and pancreatic surgery outcomes: a systematic review and meta-analysis combining human expertise and AI support (ChatGPT).

Pancreatic surgery is associated with high postoperative morbidity. The role of corticosteroids (CCS...

Virus infections and cancers: from mechanisms to therapeutics.

Viral infections are a major contributor to global cancer incidence and mortality. However, integrat...

Neuropsychological and metabolic interconnectivity in obesity, anorexia and bulimia nervosa - an integrative literature review.

A dysfunctional bi-directional signalling of plural neural networks expresses distinct metabolic dis...

Validation of a pan-ELastography Machine-learning (ELM) score to predict clinically significant portal hypertension in compensated advanced chronic liver disease.

BACKGROUND: Clinically significant portal hypertension (CSPH) drives decompensation and mortality in...

Context-Aware Multilevel Classification of Semantic Relations in Drug-Adverse Drug Reaction (ADR) Networks-Predicting Drug-Induced Liver Injury (DILI) as a Case Study.

Adverse drug reactions (ADRs) are a major concern for public health and patient safety and a burden ...

Leveraging a vendor-neutral deep learning reconstruction algorithm to reduce scan time and enhance image quality in T2-weighted liver MRI.

This study evaluated whether a vendor-neutral deep learning reconstruction (DLR) can improve image q...