Pancreatic Diseases

Tree-Based Machine Learning to Identify Predictors of Psoriasis Incidence at the Neighborhood Level: A Populational Study from Quebec, Canada.

BACKGROUND: Psoriasis is a major global health burden affecting ~ 60 million people worldwide. Exist...

Comparison of an interpretable extreme gradient boosting model and an artificial neural network model for prediction of severe acute pancreatitis.

INTRODUCTION: Acute pancreatitis (AP) that progresses to persistent organ failure is referred to as ...

The development of a deep learning model for automated segmentation of the robotic pancreaticojejunostomy.

BACKGROUND: Minimally invasive surgery provides an unprecedented opportunity to review video for ass...

Continuing Medical Education Questions: August 2024.

Article Title: Machine Learning Models for Pancreatic Cancer Risk Prediction Using Electronic Health...

Artificial intelligence in preventive cardiology.

Artificial intelligence (AI) is a field of study that strives to replicate aspects of human intellig...

Deep learning-based prediction of post-pancreaticoduodenectomy pancreatic fistula.

Postoperative pancreatic fistula is a life-threatening complication with an unmet need for accurate ...

Fully-automated multi-organ segmentation tool applicable to both non-contrast and post-contrast abdominal CT: deep learning algorithm developed using dual-energy CT images.

A novel 3D nnU-Net-based of algorithm was developed for fully-automated multi-organ segmentation in ...

Effect of insurance status on perioperative outcomes after robotic pancreaticoduodenectomy: a propensity-score matched analysis.

The influence of Medicaid or being uninsured is prevailingly thought to negatively impact a patient'...

The weight of BMI in impacting postoperative and oncologic outcomes in pancreaticoduodenectomy is attenuated by a robotic approach.

This study was undertaken to observe the effect of body mass index (BMI) on perioperative outcomes a...

nnU-Net-Based Pancreas Segmentation and Volume Measurement on CT Imaging in Patients with Pancreatic Cancer.

RATIONALE AND OBJECTIVES: To develop and validate a deep learning (DL)-based method for pancreas seg...

Response letter to the editor-Original manuscript: Machine learning versus logistic regression for the prediction of complication after pancreatoduodenectomy.

Response letter to the editor-Original manuscript: Machine learning versus logistic regression for the prediction of complication after pancreatoduodenectomy.

Use of a Perfused Cadaver for Training of Robotic Pancreaticoduodenectomy Allows for Realistic Tissue Dissection and Management of Intra-Operative Bleeding.

Innovative mesenteric Kocher maneuver during robotic pancreatoduodenectomy.

Laparoscopic and robotic distal pancreatectomy: Outcomes and the need for patient-centred evaluation.

Role of robotic surgery as an element of Enhanced Recovery After Surgery protocol in patients undergoing pancreatoduodenectomy.

BACKGROUND: Although the current trend in pancreatoduodenectomy (PD) has shifted from open surgery t...

Machine Learning Developed a MYC Expression Feature-Based Signature for Predicting Prognosis and Chemoresistance in Pancreatic Adenocarcinoma.

MYC has been identified to profoundly influence a wide range of pathologic processes in cancers. How...

Development and validation of a multimodal model in predicting severe acute pancreatitis based on radiomics and deep learning.

OBJECTIVE: Aim to establish a multimodal model for predicting severe acute pancreatitis (SAP) using ...

Diagnostic Challenges during Inflammation and Cancer: Current Biomarkers and Future Perspectives in Navigating through the Minefield of Reactive versus Dysplastic and Cancerous Lesions in the Digestive System.

In the setting of pronounced inflammation, changes in the epithelium may overlap with neoplasia, oft...

Bioinformatics and Machine Learning Methods Identified MGST1 and QPCT as Novel Biomarkers for Severe Acute Pancreatitis.

Severe acute pancreatitis (SAP) is a life-threatening gastrointestinal emergency. The study aimed to...

Automated pancreatic segmentation and fat fraction evaluation based on a self-supervised transfer learning network.

Accurate segmentation of the pancreas from abdominal computed tomography (CT) images is challenging ...