Pancreatic Diseases

Integrating Network Analysis and Machine Learning to Elucidate Chemical-Induced Pancreatic Toxicity in Zebrafish Embryos.

Zebrafish (Danio rerio) are a popular vertebrate model for high-throughput toxicity testing, serving as a model for embryonic development and disease etiology. However, standardized protocols using zebrafish tend to explore pathologies and behaviors at the organism level, rather than at the organ-specific level. This study investigates the effects of chemical exposures on pancreatic function in wh...

Dual-Mode Detection of Trypsin and Screening of Trypsin Inhibitors on the Basis of a Colorimetric/Fluorescence Sensing Probe.

Trypsin is a specific and reliable diagnostic biomarker of pancreatic function and pathological changes. Thus, detecting trypsin and screening trypsin inhibitors are highly important for clinical diagnosis and disease treatment. Herein, we propose a colorimetric/fluorescence sensing probe based on carbon quantum dots (O-CDs) and cytochrome C (Cyt C) for sensitive and specific trypsin detection and...

AutoFRS: an externally validated, annotation-free approach to computational preoperative complication risk stratification in pancreatic surgery - an experimental study.

BACKGROUND: The risk of postoperative pancreatic fistula (POPF), one of the most dreaded complications after pancreatic surgery, can be predicted from...

Variations of the chemical components and biological activities of Thymus capitatus essential oil from three regions in Palestine.

Thymus capitatus is a widely utilized medicinal plant in Palestine. The main goal of this study was to assess the phytochemical content of T. capitatu...

Development of an activity-based ratiometric electrochemical substrate for measuring circulating dipeptidyl peptidase-IV/CD26 in whole blood samples.

Dipeptidyl peptidase-IV (DPP-IV) is a circulating blood biomarker that diagnose pancreatic and thyroid cancers, as well as type 2 diabetes. Although c...

Development and external validation of a model for post-endoscopic retrograde cholangiopancreatography pancreatitis.

Post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) is a common complication in patients undergoing ERCP for choledocholithi...

Machine learning-based prediction of postoperative pancreatic fistula after laparoscopic pancreaticoduodenectomy.

BACKGROUND: Clinically relevant postoperative pancreatic fistula (CR-POPF) following laparoscopic pancreaticoduodenectomy (LPD) is a critical complica...

High-Precision Intelligent Diagnosis of Pancreatic Cancer: Flowing Diffuseness from Single to Whole.

Raman spectroscopy, as a label-free optical technique, provides a unique solution for tissue diagnosis. However, due to the limitation of point-by-poi...

Development and validation of a novel chronic pancreatitis pathological grade based on artificial intelligence.

BACKGROUND: Effective chronic pancreatitis (CP) treatment requires accurate severity evaluation, but no histopathology grading system exists. This stu...

Machine Learning-Based Radiomics in Malignancy Prediction of Pancreatic Cystic Lesions: Evidence from Cyst Fluid Multi-Omics.

The malignant potential of pancreatic cystic lesions (PCLs) varies dramatically, leading to difficulties when making clinical decisions. This study ai...

Hybrid Neural network and machine learning models with improved optimization method for gut microbiome effects on the sleep quality in patients with endometriosis.

BACKGROUND AND OBJECTIVE: Endometriosis is a chronic gynecological condition known to affect the quality of life of millions of women globally, often ...

Machine Learning to Predict Early Death Despite Pancreaticoduodenectomy.

INTRODUCTION: About 25% of patients undergoing pancreaticoduodenectomy (PD) for right-sided pancreatic ductal adenocarcinoma (PDAC) die within 1 y of ...

Evaluation of Perioperative Cardiovascular Event Risk in Gastrointestinal Surgery　- Predictive Modeling and Risk Stratification Using Machine Learning.

BACKGROUND: Preoperative risk assessment is very important to ensure surgical safety and predict postoperative complications. However, no large-scale ...

"Amide - amine + alcohol = carboxylic acid." chemical reactions as linear algebraic analogies in graph neural networks.

In deep learning methods, especially in the context of chemistry, there is an increasing urgency to uncover the hidden learning mechanisms often dubbe...

Bald eagle-optimized transformer networks with temporal-spatial mid-level features for pancreatic tumor classification.

The classification and diagnosis of pancreatic tumors present significant challenges due to their inherent complexity and variability. Traditional met...

Incorporation of explainable artificial intelligence in ensemble machine learning-driven pancreatic cancer diagnosis.

Despite the strides made in medical science, pancreatic cancer continues to be a threat, highlighting the urgent need for creative strategies to addre...

Accelerated brain aging in alcohol users: Insights from machine learning.

Artificial intelligence to predict cancer risk, are we there yet? A comprehensive review across cancer types.

Cancer remains the second leading cause of death worldwide, representing a substantial challenge to global health. Although traditional risk predictio...

Artificial intelligence models utilize lifestyle factors to predict dry eye related outcomes.

The purpose of this study is to examine and interpret machine learning models that predict dry eye (DE)-related clinical signs, subjective symptoms, a...

Automated machine learning for early prediction of systemic inflammatory response syndrome in acute pancreatitis.

BACKGROUND: Systemic inflammatory response syndrome (SIRS) is a frequent and serious complication of acute pancreatitis (AP), often associated with in...