Gastroenterology

Artificial intelligence-supported polyp detection (CADe) at colonoscopy reduces the detection of high grade dysplasia and invasive cancer.

Probiotic therapeutics: A critical review of mechanisms, clinical efficacy, and the frontier of precision microbiome modulation.

Probiotic therapeutics are evolving from generalized wellness supplements to precision Live Biotherapeutic Products aimed at specific disease targets. This review elucidates the multi-layered mechanistic framework of probiotic action, which spans ecological niche modulation, epithelial barrier reinforcement, and systemic signaling via the gut-brain axis. While clinical efficacy is established for ...

Metabolic factor-based machine learning model for mortality prediction in acute hepatitis E: Development and validation from a dual-center cohort.

BACKGROUND: Hepatitis E virus (HEV) infection remains a major cause of liver failure with high short-term mortality, yet predictive models incorporati...

Multiparametric MRI-Based Deep Learning and Radiomics for Predicting Progression-Free Survival Benefit in Patients with Hepatocellular Carcinoma Treated with Immunotherapy and Targeted Therapy Plus Transarterial Chemoembolization: A Bicentric Study.

RATIONALE AND OBJECTIVES: The non-invasive biomarkers for predicting progression-free survival (PFS) in patients with hepatocellular carcinoma (HCC) t...

[Dual role of tea consumption in gastrointestinal disease risks: analysis using a risk prediction model integrating interpretable machine learning and large language model].

OBJECTIVES: To explore the correlation of tea consumption with risks of gastrointestinal diseases using a risk prediction model integrating interpreta...

Identifying a better-prognosis pancreatic cancer from its benign inflammatory mimic: a machine learning approach with contrast-enhanced ultrasound for early intervention.

PURPOSE: Hypervascular pancreatic ductal adenocarcinoma (PDAC) and mass-forming pancreatitis (MFP) represent a classic diagnostic mimicry on contrast-...

Predicting treatment response to neoadjuvant chemotherapy in locally advanced rectal cancer: A combined deep learning and machine learning approach utilizing longitudinal multi-sequence MRI.

PURPOSE: To develop and validate deep leaning-based machine learning models using longitudinal multi-sequence MRI for predicting treatment response of...

Non-invasive prediction of Ki-67 expression in gastric cancer using AI-based dual-energy CT: a multicenter study.

OBJECTIVE: To develop and validate a machine learning model based on quantitative parameters of dual-energy CT (DECT) virtual monoenergetic images (VM...

Exploring an Intermediate Colorectal Cancer Screening Test Based on Stool Proteomics and Machine Learning for Optimizing the Selection of Patients for Colonoscopy Identified from FIT.

The fecal immunochemical test (FIT) for detecting fecal occult blood, used alone or in combination with other stool biomarkers, has been demonstrated ...

Neoadjuvant Radiation is Causally Linked to Increased Operative Time and Perioperative Blood Transfusion in Pancreatic Ductal Adenocarcinoma.

INTRODUCTION: Blood transfusion in patients undergoing surgical resection for pancreatic ductal adenocarcinoma (PDAC) is associated with worse outcome...

Evaluating the role of the main pancreatic duct in intraductal papillary mucinous neoplasm grading: A multi-structure radiomics-based machine learning approach.

PURPOSE: The purpose of this study was to evaluate the contribution of radiomics features extracted from various pancreatic structures on computed tom...

Deep Learning Integration of Endoscopic Ultrasound Features and Serum Data Reveals LTB4 as a Diagnostic and Therapeutic Target in ESCC.

BACKGROUND: Early diagnosis and accurate prediction of treatment response in esophageal squamous cell carcinoma (ESCC) remain major clinical challenge...

AI portal tract detection and characterisation for a regional analysis of steatosis and inflammation in MASLD, MASH and AIH.

AIMS: Annotation of liver biopsies for disease staging is increasingly aided by digital pathology; however, existing systems do not quantify inflammat...

Intelligent identification and targeted intervention of GRP75-caused drug resistant hepatocellular carcinoma, a study based on radiomics, machine learning, and molecular pharmacology.

BACKGROUND: Tumor heterogeneity mediated drug resistance was a core clinical challenge to improve the prognosis of patients with advanced hepatocellul...

Comment on "Machine learning model for predicting a high comprehensive complication index following rectal cancer surgery".

FOXK1 induced upregulation of KIF20A promotes hepatocellular carcinoma progression via Wnt/β-Catenin/EMT signaling.

Liver cancer ranks sixth in incidence and third in mortality worldwide, with hepatocellular carcinoma (HCC) accounting for 90% of cases. Kinesin famil...

The consensus molecular subtypes of esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) lacks a standardized classification system, resulting in inconsistent clinical management and a suboptimal p...

KRT15 identified by scRNA-Seq and machine learning as stemness regulator and prognostic biomarker in ESCC.

Postoperative recurrence and metastasis in esophageal squamous cell carcinoma (ESCC) are closely associated with cancer stem cells (CSCs), though the ...

Oncogenic function and transcriptional dynamics of MYCN in liver tumorigenesis.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality. It is often diagnosed at advanced stages and characterized by high recu...

[AI and clinical reasoning : between promises and the risks of "deskilling"].

The rise of AI in healthcare offers major potential for diagnosis and learning but also exposes to a worrying risk of "deskilling." Recent data from c...