Pancreatic Diseases

A machine learning-based model for predicting the risk of cognitive frailty in elderly patients on maintenance hemodialysis.

Elderly patients undergoing maintenance hemodialysis (MHD) face a heightened risk of cognitive frailty (CF), which significantly compromises quality of life. Early identification of at-risk individuals and timely intervention are essential. Nevertheless, current CF risk prediction models fall short in accuracy to adequately fulfill clinical requirements. This study aimed to examine the determinant...

The Role of Artificial Intelligence for Advanced Endoscopy.

Artificial intelligence (AI) application in gastroenterology has grown in the last decade and continues to evolve very rapidly. Early promising results have opened the door to explore its potential application to advanced endoscopy (AE). The aim of this review is to discuss the current state of the art and future directions of AI in AE. Current evidence suggests that AI-assisted endoscopic ultraso...

Endoscopic ultrasonography-based intratumoral and peritumoral machine learning ultrasomics model for predicting the pathological grading of pancreatic neuroendocrine tumors.

OBJECTIVES: The objective is to develop and validate intratumoral and peritumoral ultrasomics models utilizing endoscopic ultrasonography (EUS) to pre...

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...

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...

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...

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...

AntiT2DMP-Pred: Leveraging feature fusion and optimization for superior machine learning prediction of type 2 diabetes mellitus.

Pancreatic α-amylase breaks down starch into isomaltose and maltose, which are further hydrolyzed by α-glucosidase in the intestine into monosaccharid...

Development of deep learning auto-encoder algorithms for predicting alcohol use in Korean adolescents based on cross-sectional data.

Alcohol is a highly addictive substance, presenting significant global public health concerns, particularly among adolescents. Previous studies have b...

Partial directed coherence analysis of resting-state EEG signals for alcohol use disorder detection using machine learning.

INTRODUCTION: Excessive alcohol consumption negatively impacts physical and psychiatric health, lifestyle, and societal interactions. Chronic alcohol ...

Multiparametric MRI for Assessment of the Biological Invasiveness and Prognosis of Pancreatic Ductal Adenocarcinoma in the Era of Artificial Intelligence.

Pancreatic ductal adenocarcinoma (PDAC) is the deadliest malignant tumor, with a grim 5-year overall survival rate of about 12%. As its incidence and ...

Integrating traditional machine learning with qPCR validation to identify solid drug targets in pancreatic cancer: a 5-gene signature study.

BACKGROUND: Pancreatic cancer remains one of the deadliest malignancies, largely due to its late diagnosis and lack of effective therapeutic targets.

Advances in the clinical application of machine learning in acute pancreatitis: a review.

Traditional disease prediction models and scoring systems for acute pancreatitis (AP) are often inadequate in providing concise, reliable, and effecti...

mCNN-glucose: Identifying families of glucose transporters using a deep convolutional neural network based on multiple-scanning windows.

Glucose transporters are essential carrier proteins that function on the phospholipid bilayer to facilitate glucose diffusion across cell membranes. T...

Integrating artificial intelligence with endoscopic ultrasound in the early detection of bilio-pancreatic lesions: Current advances and future prospects.

The integration of Artificial Intelligence (AI) in endoscopic ultrasound (EUS) represents a transformative advancement in the early detection and mana...

Deep eutectic solvent-modified polyvinyl alcohol/chitosan thin film membrane for dye adsorption: Machine learning modeling, experimental, and density functional theory calculations.

The polyvinyl alcohol/chitosan (PVA/CS) thin film membrane was modified using a deep eutectic solvent (DES) to enhance its adsorption capability and m...

Machine learning based identification of an amino acid metabolism related signature for predicting prognosis and immune microenvironment in pancreatic cancer.

BACKGROUND: Pancreatic cancer is a highly aggressive neoplasm characterized by poor diagnosis. Amino acids play a prominent role in the occurrence and...

Deep-Learning-Based Reconstruction of Single-Breath-Hold 3 mm HASTE Improves Abdominal Image Quality and Reduces Acquisition Time: A Quantitative Analysis.

Breath-hold T2-weighted half-Fourier acquisition single-shot turbo spin echo (HASTE) magnetic resonance imaging (MRI) of the upper abdomen with a sli...

Automated CAD system for early detection and classification of pancreatic cancer using deep learning model.

Accurate diagnosis of pancreatic cancer using CT scan images is critical for early detection and treatment, potentially saving numerous lives globally...