Pancreatic Diseases

A Comprehensive Workflow for Imaging Live Insulin Secretion Events and Granules in Intact Islets.

Accurate detection of insulin secretion from pancreatic beta cells is crucial for understanding normal physiological insulin secretion and its pathophysiological counterpart in diabetic states. Traditional methods using fluorescently labeled insulin granules or dye labeling often struggle to distinguish secretion from insulin granule dynamics. We present an optimized protocol using the cell-imperm...

Enhancing liver disease diagnosis with hybrid SMOTE-ENN balanced machine learning models-an empirical analysis of Indian patient liver disease datasets.

INTRODUCTION: The liver is one of the vital organs of human body that performs some of the most crucial biological processes such as protein and biochemical synthesis, which is required for digestion and cleansing. A large number of patients are suffering from liver disease and hence it has become a life-threatening issue around the world. Annually, around 2 million people die because of liver dis...

Machine learning-driven prognostic model based on sphingolipid-related gene signature in pancreatic cancer: development and validation.

BACKGROUND: Pancreatic cancer, a highly malignant tumor with poor prognosis, lacks effective early diagnosis and treatment strategies. Sphingolipids h...

Applications of artificial intelligence in abdominal imaging.

The rapid advancements in artificial intelligence (AI) carry the promise to reshape abdominal imaging by offering transformative solutions to challeng...

The extent of Skeletal muscle wasting in prolonged critical illness and its association with survival: insights from a retrospective single-center study.

OBJECTIVE: Muscle wasting in critically ill patients, particularly those with prolonged hospitalization, poses a significant challenge to recovery and...

Clinical significance of risk factor analysis in pancreatic cancer by using supervised model of machine learning.

INTRODUCTION: Pancreatic cancer (PC) poses a significant global health challenge due to its aggressive nature, late-stage diagnosis, and high mortalit...

Developing a predictive model for septic shock risk in acute pancreatitis patients using interpretable machine learning algorithms.

BACKGROUND: Septic shock is a severe complication of acute pancreatitis (AP), often associated with poor prognosis. This study aims to analyze the cli...

Prognostic model identification of ribosome biogenesis-related genes in pancreatic cancer based on multiple machine learning analyses.

BACKGROUND: Pancreatic cancer is a highly aggressive cancer characterized by low survival rate. Enhanced ribosome biogenesis may be associated with tu...

Development of a Heart Rate Variability Based Ambulatory Stress Detection Model for Clinical Populations.

Biosensor-based, real-time stress detection has generated clinical interest for the purpose of driving just-in-time interventions that support recover...

Mechanisms underlying obesity-malignancy connection: a systematic narrative review.

The association between obesity and cancer risk carries substantial public health ramifications as obesity promotes cancer advancement via many cellul...

End-to-end prognostication in pancreatic cancer by multimodal deep learning: a retrospective, multicenter study.

OBJECTIVES: Pancreatic cancer treatment plans involving surgery and/or chemotherapy are highly dependent on disease stage. However, current staging sy...

Innate immune cell barrier-related genes inform precision prognosis in pancreatic cancer.

INTRODUCTION: Pancreatic cancer (PC) remains a lethal malignancy with limited treatment options. The role of innate immune cell barrier-related genes ...

Diagnostic risk prediction models for upper gastrointestinal cancers: A systematic review.

Upper gastrointestinal (UGI) cancers are often detected late. Risk prediction models could facilitate earlier detection by identifying patients at ris...

Plasma and Urine Circulating Tumor DNA Methylation Profiles for Non-Invasive Pancreatic Ductal Adenocarcinoma Detection: Significant Findings in Plasma Only.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with limited treatment options, and early detection remains challenging due to the lack...

Towards automating risk stratification of intraductal papillary mucinous Neoplasms: Artificial intelligence advances beyond human expertise with confocal laser endomicroscopy.

BACKGROUND AND AIMS: Endoscopic Ultrasound (EUS)-guided needle-based confocal laser endomicroscopy (nCLE) enables real-time microscopic visualization ...

Graphene Oxide-Modulated CMC/PVA Films with on-Demand Shape Recovery and Self-Healing Performance.

With the advancement of artificial intelligence technologies, shape-memory polymers (SMPs) have attracted significant research interest due to their r...

New Insights into the Diagnosis and Treatment of Hepatocellular Carcinoma.

Hepatocellular carcinoma remains one of the leading contributors to global cancer mortality, frequently stemming from chronic liver conditions, such a...

Cognitive Dysfunction in the Addictions (CDiA): protocol for a neuron-to-neighbourhood collaborative research program.

Substance use disorders (SUDs), including Alcohol Use Disorder, are pressing global public health problems. Executive functions (EFs) are prominently ...

Pancreas segmentation using AI developed on the largest CT dataset with multi-institutional validation and implications for early cancer detection.

Accurate and fully automated pancreas segmentation is critical for advancing imaging biomarkers in early pancreatic cancer detection and for biomarker...

Evaluation of tumour pseudocapsule using computed tomography-based radiomics in pancreatic neuroendocrine tumours to predict prognosis and guide surgical strategy: a cohort study.

BACKGROUND: To date, indications for a surgical approach of small pancreatic neuroendocrine tumours (PanNETs) remain controversial. This cohort study ...