Pancreatic Diseases

Application of Artificial Intelligence to Gastroenterology and Hepatology.

Since 2010, substantial progress has been made in artificial intelligence (AI) and its application to medicine. AI is explored in gastroenterology for endoscopic analysis of lesions, in detection of cancer, and to facilitate the analysis of inflammatory lesions or gastrointestinal bleeding during wireless capsule endoscopy. AI is also tested to assess liver fibrosis and to differentiate patients w...

A machine learning algorithm predicts molecular subtypes in pancreatic ductal adenocarcinoma with differential response to gemcitabine-based versus FOLFIRINOX chemotherapy.

PURPOSE: Development of a supervised machine-learning model capable of predicting clinically relevant molecular subtypes of pancreatic ductal adenocarcinoma (PDAC) from diffusion-weighted-imaging-derived radiomic features.

Validation of an alcohol misuse classifier in hospitalized patients.

BACKGROUND: Current modes of identifying alcohol misuse in hospitalized patients rely on self-report questionnaires and diagnostic codes that have lim...

Deep learning for World Health Organization grades of pancreatic neuroendocrine tumors on contrast-enhanced magnetic resonance images: a preliminary study.

PURPOSE: The World Health Organization (WHO) grading system of pancreatic neuroendocrine tumor (PNET) plays an important role in the clinical decision...

Technical and Clinical Factors Affecting Success Rate of a Deep Learning Method for Pancreas Segmentation on CT.

PURPOSE: Accurate pancreas segmentation has application in surgical planning, assessment of diabetes, and detection and analysis of pancreatic tumors....

Preoperative Prediction of Pancreatic Neuroendocrine Neoplasms Grading Based on Enhanced Computed Tomography Imaging: Validation of Deep Learning with a Convolutional Neural Network.

INTRODUCTION: The pathological grading of pancreatic neuroendocrine neoplasms (pNENs) is an independent predictor of survival and indicator for treatm...

How Much Was the Elective Lymph Node Region Covered in Involved-Field Radiation Therapy for Locally Advanced Pancreatic Cancer? Evaluation of Overlap Between Gross Target Volume and Celiac Artery-Superior Mesenteric Artery Lymph Node Regions.

PURPOSE: The purpose of this study was to investigate the overlaps between gross target volume (GTV) and the celiac artery (CA) and superior mesenteri...

Nutritional, biochemical and microbiological composition of Mart. sap in Burkina Faso.

The palmyra palm Mart. grow wild and gives natural stands in several localities of central-eastern and eastern regions of Burkina Faso. This work aim...

Profiling of Exosomal Biomarkers for Accurate Cancer Identification: Combining DNA-PAINT with Machine- Learning-Based Classification.

Exosomes are endosome-derived vesicles enriched in body fluids such as urine, blood, and saliva. So far, they have been recognized as potential biomar...

Alcohol outlets and firearm violence: a place-based case-control study using satellite imagery and machine learning.

INTRODUCTION: This article proposes a novel method for matching places based on visual similarity, using high-resolution satellite imagery and machine...

ASO Author Reflections: Formalization of Robotic Central Pancreatectomy Focusing on the Reconstruction of Pancreatic Digestive Continuity.

Performance of deep learning for differentiating pancreatic diseases on contrast-enhanced magnetic resonance imaging: A preliminary study.

PURPOSE: The purpose of this study was to evaluate the ability of deep learning to differentiate pancreatic diseases on contrast-enhanced magnetic res...

Annotated normal CT data of the abdomen for deep learning: Challenges and strategies for implementation.

PURPOSE: The purpose of this study was to report procedures developed to annotate abdominal computed tomography (CT) images from subjects without panc...

Inferring the Disease-Associated miRNAs Based on Network Representation Learning and Convolutional Neural Networks.

Identification of disease-associated miRNAs (disease miRNAs) are critical for understanding etiology and pathogenesis. Most previous methods focus on ...

Response to repeat echoendoscopic celiac plexus neurolysis in pancreatic cancer patients: A machine learning approach.

BACKGROUND: /Objectives: Efficacy of repeat echoendoscopic celiac plexus neurolysis is still unclear. Aim of the study was to assess the efficacy of r...

Recurrent Saliency Transformation Network for Tiny Target Segmentation in Abdominal CT Scans.

We aim at segmenting a wide variety of organs, including tiny targets (e.g., adrenal gland), and neoplasms (e.g., pancreatic cyst), from abdominal CT ...

A newly developed transparent and flexible one-transistor memory device using advanced nanomaterials for medical and artificial intelligence applications.

 Artificial intelligence (AI) integrated circuits (IC) have memory devices as the key component. Due to more complex algorithms and architectures requ...

Artificial neural networks accurately predict intra-abdominal infection in moderately severe and severe acute pancreatitis.

OBJECTIVE: The aim of this study was to evaluate the efficacy of artificial neural networks (ANN) in predicting intra-abdominal infection in moderatel...

Clinically Applicable Deep Learning Algorithm Using Quantitative Proteomic Data.

Deep learning (DL), a type of machine learning approach, is a powerful tool for analyzing large sets of data that are derived from biomedical sciences...

Synthesis and Swelling Behavior of Sodium Alginate/Poly(vinyl alcohol) Hydrogels.

OBJECTIVES: Hydrogels are macromolecular networks able to absorb and release water/biological fluids in a reverse-phase manner, in response to specifi...