Pancreatic Diseases

Minimally invasive (laparoscopic and robot-assisted) versus open approach for central pancreatectomies: a single-center experience.

BACKGROUND: There continues to be an interest in minimally invasive approaches to pancreatic surgery. At our institution, there has been a progressive change from an open to minimally invasive surgery (MIS) (laparoscopic, robotic, or laparoscopic-robotic) approach for central pancreatectomies (CP). The aim of this study was to evaluate surgical outcomes with open CP (O-CP) versus minimally invasiv...

R-JaunLab: Automatic Multi-Class Recognition of Jaundice on Photos of Subjects with Region Annotation Networks.

Jaundice occurs as a symptom of various diseases, such as hepatitis, the liver cancer, gallbladder or pancreas. Therefore, clinical measurement with special equipment is a common method that is used to identify the total serum bilirubin level in patients. Fully automated multi-class recognition of jaundice combines two key issues: (1) the critical difficulties in multi-class recognition of jaundic...

Surgical training model and safe implementation of robotic pancreatoduodenectomy in Japan: a technical note.

BACKGROUND: Growing evidence for the advantages of robotic pancreatoduodenectomy (RPD) has been demonstrated internationally. However, there has been ...

Proposed training pathway with initial experience to set up robotic hepatobiliary and pancreatic service.

Although robot-assisted hepatobiliary and pancreatic (HPB) surgery has gained momentum over the last 2 decades, only a handful of units in the world p...

Robotic Total Pancreatectomy: A Novel Pancreatic Head-First Approach (with Video).

BACKGROUND: The development of the Da Vinci robotic platform has drastically altered the paradigm of minimal invasive pancreatic surgery. However, the...

Artificial intelligence: a critical review of current applications in pancreatic imaging.

The applications of artificial intelligence (AI), including machine learning and deep learning, in the field of pancreatic disease imaging are rapidly...

Discriminating the single-cell gene regulatory networks of human pancreatic islets: A novel deep learning application.

Analysis of single-cell pancreatic data can play an important role in understanding various metabolic diseases and health conditions. Due to the spars...

[Robot-assisted Distal Pancreatectomy with En Bloc Celiac Axis Resection (Modified Appleby Procedure) after Neoadjuvant Therapy].

Pancreatic carcinoma in the body and on the left side of the mesentericoportal axis is often only detected in late stages owing to unspecific or even ...

Deep Learning-Based Annotation Transfer between Molecular Imaging Modalities: An Automated Workflow for Multimodal Data Integration.

An ever-increasing array of imaging technologies are being used in the study of complex biological samples, each of which provides complementary, occa...

Combined Spiral Transformation and Model-Driven Multi-Modal Deep Learning Scheme for Automatic Prediction of TP53 Mutation in Pancreatic Cancer.

Pancreatic cancer is a malignant form of cancer with one of the worst prognoses. The poor prognosis and resistance to therapeutic modalities have been...

Outcomes of a Multicenter Training Program in Robotic Pancreatoduodenectomy (LAELAPS-3).

OBJECTIVE: To assess feasibility and safety of a multicenter training program in robotic pancreatoduodenectomy (RPD) adhering to the IDEAL framework f...

Visual Analytics of a Computer-Aided Diagnosis System for Pancreatic Lesions.

Machine learning is a powerful and effective tool for medical image analysis to perform computer-aided diagnosis (CAD). Having great potential in impr...

An Artificial Neural Networks Model for Early Predicting In-Hospital Mortality in Acute Pancreatitis in MIMIC-III.

BACKGROUND: Early and accurate evaluation of severity and prognosis in acute pancreatitis (AP), especially at the time of admission is very significan...

Comparison of MPL-ANN and PLS-DA models for predicting the severity of patients with acute pancreatitis: An exploratory study.

OBJECTIVE: Acute pancreatitis (AP) is a common inflammatory disorder that may develop into severe AP (SAP), resulting in life-threatening complication...

Prediction and interpretation of cancer survival using graph convolution neural networks.

The survival rate of cancer has increased significantly during the past two decades for breast, prostate, testicular, and colon cancer, while the brai...

Improving prognostic performance in resectable pancreatic ductal adenocarcinoma using radiomics and deep learning features fusion in CT images.

As an analytic pipeline for quantitative imaging feature extraction and analysis, radiomics has grown rapidly in the past decade. On the other hand, r...

GVES: machine learning model for identification of prognostic genes with a small dataset.

Machine learning may be a powerful approach to more accurate identification of genes that may serve as prognosticators of cancer outcomes using variou...

Pancreatic fistulas following distal pancreatectomy are unrelated to the texture quality of the pancreas.

PURPOSE: The relevance of pancreatic texture for pancreatic fistula (POPF) formation after distal pancreatectomy (DP) remains ill defined. Recent POPF...

Fully end-to-end deep-learning-based diagnosis of pancreatic tumors.

Artificial intelligence can facilitate clinical decision making by considering massive amounts of medical imaging data. Various algorithms have been i...

Pure and Hybrid Deep Learning Models can Predict Pathologic Tumor Response to Neoadjuvant Therapy in Pancreatic Adenocarcinoma: A Pilot Study.

BACKGROUND: Neoadjuvant therapy may improve survival of patients with pancreatic adenocarcinoma; however, determining response to therapy is difficult...