Gastroenterology

Explicit modeling of beam geometry improves three-dimensional dose prediction for esophageal cancer radiotherapy under heterogeneous beam configurations.

PURPOSE: Deep learning-based 3D dose prediction boosts radiotherapy planning efficiency and consistency, yet most models rely solely on anatomical data and assume homogeneous beam configurations, impairing their robustness in esophageal cancer intensity-modulated radiotherapy (IMRT) with heterogeneous beam arrangements. This study explored whether explicit beam geometry modeling enhances voxel-lev...

Deciphering the multi-target mechanism of Magnolia officinalis in irritable bowel syndrome with diarrhea: A combined network pharmacology, machine learning, and in vivo validation study.

BACKGROUND: The bark of Magnolia officinalis Rehder & E. Wilson, used in TCM for abdominal distension, pain, and diarrhea, aligns with IBS-D symptoms. It is now supported by evidence for its multi-component, multi-target action. This study aims to elucidate the core bioactive components and their mechanisms against IBS-D. To achieve this, we employed an analytical strategy that uses machine learni...

Global incidence patterns of early-onset gastrointestinal cancers and their ecological associations with behavioural risk factors.

BACKGROUND: Early-onset gastrointestinal cancers (EOGIC) are increasingly recognised as an urgent global health concern. We aimed to describe the glob...

Automated deep learning model for predicting pathological complete response in rectal cancer: A tool to organ-preserving strategies.

BACKGROUND: Accurate identification of pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal canc...

Microbiome in Gastrointestinal Tumors: Implications in Oncogenesis and Therapeutic Response : Microbiome in Gastrointestinal Tumors.

PURPOSE OF REVIEW: To provide an updated overview of the role of the human microbiome in the initiation, progression, and therapeutic response of gast...

A pre-trained foundation model framework for multiplanar MRI classification of extramural vascular invasion and mesorectal fascia invasion in rectal cancer.

OBJECTIVES: Accurate MRI-based identification of extramural vascular invasion (EVI) and mesorectal fascia invasion (MFI) is crucial for risk-stratifie...

Identification of replication factor C subunit 4 as a potential therapeutic target in esophageal squamous cell carcinoma based on bioinformatic analysis and machine learning.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is one of the highly lethal and aggressive malignant tumors worldwide. To effectively prevent an...

Non-invasive predictive model for incidental gallbladder carcinoma based on multimodal features: Integrating clinical data, MRI radiomics, and deep transfer learning features.

Gallbladder carcinoma, among the most prevalent malignancies of the biliary system, often presents with insidious early symptoms. Delayed diagnosis of...

Autonomous RCM-less endoscope control: integrating force-based pivoting with deep learning visual servoing.

Robotic endoscope holders improve visual stability, yet enforcing a fixed remote center of motion (RCM) often induces lateral interaction forces due t...

Machine learning outperforms serum creatinine for early risk stratification of hepatorenal syndrome: a prospective single-center validation.

BACKGROUND: The early diagnosis of hepatorenal syndrome (HRS) is constrained by the reliance on serum creatinine, a biomarker with well-documented lim...

Machine learning based hepatic safety score predicts decompensation in hepatocellular carcinoma systemic therapy.

Hepatocellular carcinoma (HCC) frequently coexists with portal hypertension, significantly increasing the risk of hepatic decompensation (HD) and vari...

Radiomics analysis of restaging MRI for detection of pathological complete response in locally advanced rectal cancer.

PURPOSE: magnetic resonance imaging (MRI)-based radiomics has emerged as a promising approach for non-invasive prediction of treatment response in rec...

A novel endoscopic ultrasound system assisted by artificial intelligence for the recognition of pancreatic parenchyma and the detection of solid/cystic lesions.

Fully Automated Colon Delineation and Volume Estimation in T2-Weighted MRI with a 2D U-Net.

Artificial intelligence has the potential to provide an objective, accurate and fast evaluation of the colon for clinical assessment of gastrointestin...

Building an Ontology-Based Cohort of Liver Cancer Imaging Data for AI Development on the European Federated Platform EUCAIM.

Hepatocellular carcinoma (HCC) is steadily increasing in incidence worldwide and requires data-driven approaches to improve diagnosis, prognosis, and ...

Multimodal Graph-Based Model for Discrete-Time Survival Prediction in Liver Cancer.

Liver cancer is a leading cause of cancer mortality; hepatocellular carcinoma (HCC), its predominant form, requires accurate survival prediction to gu...

Random Forest Model for the Prediction of Herbal-Induced Liver Injury: Application to Molecules from the West African Pharmacopoeia.

Herbal medicines play a crucial role in primary healthcare across West Africa, yet their potential for liver toxicity remains poorly documented. Predi...

CACRC-Pan: A Concept Annotated Case Report Corpus and Processing Pipeline for Rare Pancreatic Diseases.

We introduce CACRC-Pan, a corpus of case reports for six rare pancreatic diseases (AIP1-2, CF, HCP, PS and SDS) annotated at two concept levels: token...

Extraction of Endoscopic Markers from Clinical Notes in Italian Patients with Autoimmune Atrophic Gastritis Using Small Language Models.

While Large Language Models (LLMs) hold great potential for clinical applications, their use is limited by concerns regarding data privacy, high compu...

Uncovering Topics in Dutch Patient Messages in Inflammatory Bowel Disease: A Comparative Study of Embedding Models for Neural Topic Modeling.

This study applied natural language processing to identify common topics in 12,054 Dutch patient-provider messages in inflammatory bowel disease. Usin...