Pancreatic Diseases

Explainable Prediction of ICU Transfer in Acute Pancreatitis: A Neural Network Model With SHAP Interpretability for Clinical Decision Support.

OBJECTIVE: Acute pancreatitis (AP) is a life-threatening disorder commonly observed in emergency departments. Patients with acute pancreatitis may necessitate transfer to the intensive care unit (ICU) if standard treatments prove ineffective. The development of a machine learning (ML) model that can precisely forecast the necessity for ICU admission in patients with acute pancreatitis might dramat...

Predictive Value of Machine Learning for Mortality Risk in Acute Pancreatitis: A Systematic Review and Meta-Analysis.

BACKGROUND: Acute pancreatitis (AP), a common acute abdominal disease, has a high mortality rate in severe cases. Accurate mortality prediction is crucial for clinical decision-making. Machine learning (ML) models have shown potential in predicting AP mortality, aiding clinicians in understanding prediction mechanisms and formulating personalized treatment plans. OBJECTIVE: This study evaluates an...

Risk Prediction Models for Post-Endoscopic Retrograde Cholangiopancreatography Pancreatitis: A Systematic Review and Meta-Analysis.

BACKGROUND: Endoscopic retrograde cholangiopancreatography (ERCP) serves as an essential procedure for diagnosing and treating pancreaticobiliary diso...

Risk factors and early clinical outcomes of acute pancreatitis: A retrospective case series from Kyrgyzstan.

BACKGROUND: Acute pancreatitis (AP) is a common gastrointestinal emergency characterized by unpredictable severity. Early identification of patients a...

Transferability of radiomics models between deep learning and conventional CT reconstruction algorithms: A task-based assessment for stratifying acute pancreatitis severity.

BACKGROUND: Extensive evidence has demonstrated the superior image quality achieved through deep learning-based reconstruction algorithms. However, gi...

Usefulness of Artificial Intelligence for Surgical Support in Robot-assisted Distal Pancreatectomy: A Preliminary Case Report.

BACKGROUND/AIM: The incidence of postoperative complications in minimally-invasive surgery for pancreatic disease remains a concern. The application o...

Multi-Omics and Machine Learning-Driven Discovery of ABCC8 (SUR1) for Diabetes Mellitus: Integrating Molecular Insights on Nigella sativa Bioactives and Sulfonylurea.

Diabetes mellitus is a chronic metabolic disorder characterized by hyperglycemia and pancreatic β-cell dysfunction. The ATP-sensitive potassium KATP c...

X-LAT-Net: An Interpretable Lightweight Axial Transformer Network for Pancreatic CT Segmentation.

Accurate segmentation of the pancreas in CT images is notoriously difficult due to its deep-seated anatomical position, complex morphological variatio...

CGE26-143: Radiomics and Machine Learning Models for Predicting Early Recurrence After Pancreatic Cancer Resection: A Systematic Review.

HSR26-230: Machine Learning Models Predict Depression Among Pancreatic and Head and Neck Cancers.

Technical challenges and quality considerations for dissolving microneedles.

Dissolving microneedles (DMNs) deliver therapeutic molecules by bypassing the stratum corneum upon skin insertion. While DMNs show potential for trans...

Whole Metagenomic Profiling Identifies a Gut Microbial Signature for Chronic Pancreatitis via Machine Learning.

BACKGROUND: Pancreatitis significantly alters the microbial composition of the oral and intestinal compartments, causing dysbiosis that may contribute...

A method for the assessment of rheumatoid arthritis using neural network supported static and dynamic thermal analysis.

Rheumatoid arthritis (RA) is a chronic inflammatory disease characterized by pain, swelling, stiffness, and loss of joint function, making early diagn...

Machine learning prediction of common bile duct stones using synthetic data to guide emergency ERCP decisions.

Endoscopic retrograde cholangiopancreatography (ERCP) remains the standard for common bile duct (CBD) stone removal. However, current guidelines often...

Hypergraph Representations of Single-Cell RNA Sequencing Data for Improved Cell Clustering.

MOTIVATION: Single-cell RNA sequencing (scRNA-seq) data analysis is often performed using network projections that produce co-expression networks. The...

Exploring the association between Frailty Index and Knee osteoarthritis in middle-aged and older Chinese adults: A cross-sectional analysis of data from the China Health and Retirement Longitudinal Study.

OBJECTIVE: To explore the relationship between Frailty Index (FI) and Knee osteoarthritis (KOA) in Chinese people aged 45 and above. METHODS: Data on ...

Leveraging Machine Learning to Predict Mental Health Referral Follow-up Among US Military Personnel.

BACKGROUND: Noncompliance with mental health referrals among US military personnel remains a significant barrier to care. Operational deployments and ...

Integrating liquid biopsies and artificial intelligence for early cancer detection: A systematic review and meta-analysis.

INTRODUCTION: The latest generation of liquid biopsies incorporates multi-omic features, including genomics, methylomics, and fragmentomics. Machine l...

PNET-PRISM: a multicenter-validated radiomics nomogram for noninvasive grading of pancreatic neuroendocrine tumors.

BACKGROUND: Accurate preoperative grading of pancreatic neuroendocrine tumors (PNETs) is essential for optimal treatment selection, yet endoscopic ult...

Clinical priors-inspired privileged knowledge distillation for reliable pancreatic lesion classification.

Accurate classification of pancreatic lesions is critical for guiding treatment decisions, with computed tomography (CT) being the primary modality ow...