Pancreatic Diseases

Machine learning prediction of dropping out of outpatients with alcohol use disorders.

BACKGROUND: Alcohol use disorder (AUD) is a chronic disease with a higher recurrence rate than that of other mental illnesses. Moreover, it requires continuous outpatient treatment for the patient to maintain abstinence. However, with a low probability of these patients to continue outpatient treatment, predicting and managing patients who might discontinue treatment becomes necessary. Accordingly...

Modeling Texture in Deep 3D CNN for Survival Analysis.

Radiomics has shown remarkable potential for predicting the survival outcome for various types of cancers such as pancreatic ductal adenocarcinoma (PDAC). However, to date, there has been limited research using convolutional neural networks (CNN) with radiomic methods for this task, due to their requirement for large training sets. To overcome this issue, we propose a new type of radiomic descript...

Deep Semantic Segmentation Feature-Based Radiomics for the Classification Tasks in Medical Image Analysis.

Recently, an emerging trend in medical image classification is to combine radiomics framework with deep learning classification network in an integrat...

Robotic Dual-Console Distal Pancreatectomy: Could it be Considered a Safe Approach and Surgical Teaching even in Pancreatic Surgery? A Retrospective Observational Study Cohort.

BACKGROUND: The study aims to assess the safety and feasibility of the robotic dual-console during a robotic distal pancreatectomy METHODS: The data o...

Learning Carbohydrate Digestion and Insulin Absorption Curves Using Blood Glucose Level Prediction and Deep Learning Models.

Type 1 diabetes is a chronic disease caused by the inability of the pancreas to produce insulin. Patients suffering type 1 diabetes depend on the appr...

Quick Annotator: an open-source digital pathology based rapid image annotation tool.

Image-based biomarker discovery typically requires accurate segmentation of histologic structures (e.g. cell nuclei, tubules, and epithelial regions) ...

Predicting pathogenic non-coding SVs disrupting the 3D genome in 1646 whole cancer genomes using multiple instance learning.

Over the past years, large consortia have been established to fuel the sequencing of whole genomes of many cancer patients. Despite the increased abun...

Sclareol Inhibits Hypoxia-Inducible Factor-1α Accumulation and Induces Apoptosis in Hypoxic Cancer Cells.

The hypoxia in solid tumors is associated with the resistance to chemo/radiotherapy. Hypoxia-inducible factor-1 (HIF-1) plays a key role in cell remo...

A Semiautomated Deep Learning Approach for Pancreas Segmentation.

Accurate pancreas segmentation from 3D CT volumes is important for pancreas diseases therapy. It is challenging to accurately delineate the pancreas d...

Multi-institutional development and external validation of machine learning-based models to predict relapse risk of pancreatic ductal adenocarcinoma after radical resection.

BACKGROUND: Surgical resection is the only potentially curative treatment for pancreatic ductal adenocarcinoma (PDAC) and the survival of patients aft...

Eye-Movement-Controlled Wheelchair Based on Flexible Hydrogel Biosensor and WT-SVM.

To assist patients with restricted mobility to control wheelchair freely, this paper presents an eye-movement-controlled wheelchair prototype based on...

Deep learning image reconstruction algorithm for pancreatic protocol dual-energy computed tomography: image quality and quantification of iodine concentration.

OBJECTIVES: To evaluate the image quality and iodine concentration (IC) measurements in pancreatic protocol dual-energy computed tomography (DECT) rec...

Effect of deep learning image reconstruction in the prediction of resectability of pancreatic cancer: Diagnostic performance and reader confidence.

OBJECTIVE: To assess the diagnostic performance and reader confidence in determining the resectability of pancreatic cancer at computed tomography (CT...

Improved unsupervised physics-informed deep learning for intravoxel incoherent motion modeling and evaluation in pancreatic cancer patients.

PURPOSE: Earlier work showed that IVIM-NET , an unsupervised physics-informed deep neural network, was faster and more accurate than other state-of-th...

Predicting changes in substance use following psychedelic experiences: natural language processing of psychedelic session narratives.

: Experiences with psychedelic drugs, such as psilocybin or lysergic acid diethylamide (LSD), are sometimes followed by changes in patterns of tobacco...

Can we screen for pancreatic cancer? Identifying a sub-population of patients at high risk of subsequent diagnosis using machine learning techniques applied to primary care data.

BACKGROUND: Pancreatic cancer (PC) represents a substantial public health burden. Pancreatic cancer patients have very low survival due to the difficu...

Domain adaptation for segmentation of critical structures for prostate cancer therapy.

Preoperative assessment of the proximity of critical structures to the tumors is crucial in avoiding unnecessary damage during prostate cancer treatme...

State of the art robotic distal pancreatectomy: a review of the literature.

Minimally invasive distal pancreatectomy has become increasingly used in practice. While laparoscopic approach is the most commonly used technique, ro...

An study of lipase inhibitory peptides obtained from de-oiled rice bran.

De-oiled rice bran (DORB) is a potentially useful by-product of the rice bran oil industry. DORB may prove to be an important protein source, and also...

Pancreas segmentation with probabilistic map guided bi-directional recurrent UNet.

Pancreas segmentation in medical imaging is of great significance for clinical pancreas diagnostics and treatment. However, the large population varia...