Gastroenterology

Second-line chemotherapy after gemcitabine plus nab-paclitaxel in metastatic pancreatic cancer: comparative outcomes and AI-guided treatment selection.

BACKGROUND: International guidelines recommend 5FU/LV, Nal-IRI + 5FU/LV, FOLFIRI, FOLFOX, or (m)FOLFIRINOX as second-line (2 L) chemotherapy for patients with metastatic pancreatic ductal adenocarcinoma (mPDAC) after failure of gemcitabine+Nab-paclitaxel (GnP). However, a head-to-head comparison has not been performed. PATIENTS AND METHODS: We conducted an observational cohort study of consecutive...

Hypoxia-related and immune phenotype-related fusion model for non-invasive prognostication of hepatocellular carcinoma treated by TACE: a multicentre study.

BACKGROUND: Survival outcomes after transarterial chemoembolisation (TACE) vary in hepatocellular carcinoma (HCC) patients, and existing prognostic scores and imaging models often lack generalisability and biological interpretability. OBJECTIVE: To develop and validate a multimodal prognostication model for HCC that allows for a precise assessment of survival outcomes of HCC patients receiving TAC...

Comment on "The optimal labelling method for artificial intelligence-assisted polyp detection in colonoscopy".

Development and Validation of a Machine Learning Model for Predicting 3-Year Overall Survival After Transjugular Intrahepatic Portosystemic Shunt: A Retrospective Multicenter Study.

BACKGROUND AND AIMS: Predicting overall survival (OS) in cirrhotic patients undergoing transjugular intrahepatic portosystemic shunt (TIPS) remains ch...

The ATF5-GPER1 axis drives female protection in hepatocellular carcinoma through dual tumor-suppressive and immune-modulatory mechanisms.

Hepatocellular carcinoma (HCC) exhibits marked sexual dimorphism, with females demonstrating superior survival, yet the underlying molecular mechanism...

Explainable artificial intelligence for personalized prognosis in pancreatic cancer: A nationwide study from Taiwan.

Pancreatic cancer is highly aggressive with poor outcomes; current artificial intelligence (AI) prognostic models often lack interpretability and unde...

Associations between 12 insulin resistance surrogates with metabolic dysfunction-associated steatotic liver disease risk and all-cause mortality: data from the NHANES III (1988-1994).

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) has been shown to be intimately linked to the presence of insulin resista...

Advances and opportunities in measuring dietary intake: from omics to AI.

Accurate measurement of dietary intake remains a cornerstone challenge in optimizing the efficacy of nutritional interventions in human disease. Tradi...

Artificial intelligence and capsule endoscopy.

The advent of artificial intelligence (AI) is revolutionizing today's clinical practice, particularly in gastroenterology, where capsule endoscopy (CE...

Keros-Net: a convolutional block attention module-squeeze-and-excitation-integrated hybrid learning framework for olfactory fossa depth classification.

PURPOSE: This study aimed to develop a hybrid decision support framework combining deep learning (DL) and machine learning (ML) to automatically class...

A Machine Learning-Based Clinical Tool for Predicting Inadequate Bowel Preparation: Development and Validation.

OBJECTIVES: Colonoscopy is an essential tool for diagnosing and treating colorectal diseases, with bowel preparation serving as a key determinant of i...

AI-Derived Electronic Tumor Marker For Cancer Antigen 19-9 Nonproducers With Pancreatic Ductal Adenocarcinoma.

IMPORTANCE: Cancer antigen 19-9 (CA19-9) is used to assess treatment response among patients with pancreatic ductal adenocarcinoma (PDAC); however, ne...

An artificial intelligence-powered digital pathology platform to support large-scale deworming programs against soil-transmitted helminthiasis and intestinal schistosomiasis in resource-limited settings.

BACKGROUND: The World Health Organization (WHO) has emphasised the need for innovative diagnostic tools to support the control and elimination of negl...

Origami-inspired grasper for safe tissue manipulation.

The OriGrasp can flatten for storage and deploy as a compliant grasper for firm yet safe handling of bowel tissue.

Text-guided automatic segmentation of clinical target volume in rectal cancer radiotherapy.

OBJECTIVE: Current automatic segmentation models in radiotherapy, which are predominantly unimodal and image-based, have limited generalizability due ...

Token-guided multimodal prognosis in hepatocellular carcinoma: a framework steered by tumour-stroma ratio.

BACKGROUND: The tumour-stroma ratio (TSR) is a potential prognostic indicator, yet hindered by quantification challenges and conflicting reports. OBJE...

ChatGPT in liver transplantation: Current applications, limitations, and future directions.

Liver transplantation (LT) remains the optimal life-saving intervention for patients with end-stage liver disease. Despite the recent advances in LT s...

Prospective evaluation of artificial intelligence-assisted monitoring of the effective withdrawal time on adenoma detection.

BACKGROUND/AIMS: Standard withdrawal time (SWT) is a recognized colonoscopy quality metric but may not capture mucosal examination quality. We develop...

Development of a convolutional neural network for the endoscopic classification of pouchitis in patients after restorative proctocolectomy.

BACKGROUND AND AIMS: The aim of this prospective single-center study is to train convolutional neural networks (CNNs) to detect the presence of pouchi...

High-Speed Instance Segmentation for Endoscopic Spine Surgery: Multicenter Validation and Inference Speed Evaluation.

Study DesignRetrospective Multicenter Cohort Study.ObjectivesTo develop and validate an AI-based high-speed multi-class instance segmentation system f...