Pancreatic Diseases

Predicting alcohol dependence from multi-site brain structural measures.

To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance imaging, it may be useful to develop classification models that are explicitly generalizable to unseen sites and populations. This problem was explored in a mega-analysis of previously published datasets from 2,034 AD and comparison participants spanning 27 sites curated by the ENIGMA Addiction Workin...

Deep learning analysis for the detection of pancreatic cancer on endosonographic images: a pilot study.

BACKGROUND/PURPOSE: The application of artificial intelligence to clinical diagnostics using deep learning has been developed in recent years. In this study, we developed an original computer-assisted diagnosis (CAD) system using deep learning analysis of EUS images (EUS-CAD), and assessed its ability to detect pancreatic ductal carcinoma (PDAC), using control images from patients with chronic pan...

Improving the slice interaction of 2.5D CNN for automatic pancreas segmentation.

PURPOSE: Volumetric pancreas segmentation can be used in the diagnosis of pancreatic diseases, the research about diabetes and surgical planning. Sinc...

SHIFT: speedy histological-to-immunofluorescent translation of a tumor signature enabled by deep learning.

Spatially-resolved molecular profiling by immunostaining tissue sections is a key feature in cancer diagnosis, subtyping, and treatment, where it comp...

Prognostic value of FDG-PET radiomics with machine learning in pancreatic cancer.

Patients with pancreatic cancer have a poor prognosis, therefore identifying particular tumor characteristics associated with prognosis is important. ...

Utilisation of artificial intelligence for the development of an EUS-convolutional neural network model trained to enhance the diagnosis of autoimmune pancreatitis.

OBJECTIVE: The diagnosis of autoimmune pancreatitis (AIP) is challenging. Sonographic and cross-sectional imaging findings of AIP closely mimic pancre...

Prediction of Type II Diabetes Onset with Computed Tomography and Electronic Medical Records.

Type II diabetes mellitus (T2DM) is a significant public health concern with multiple known risk factors (, body mass index (BMI), body fat distributi...

Cryostructuring of Polymeric Systems : Application of Deep Neural Networks for the Classification of Structural Features Peculiar to Macroporous Poly(vinyl alcohol) Cryogels Prepared without and with the Additives of Chaotropes or Kosmotropes.

Macroporous poly(vinyl alcohol) cryogels (PVACGs) are physical gels formed via cryogenic processing of polymer solutions. The properties of PVACGs dep...

The relation of CT quantified pancreatic fat index with visceral adiposity and hepatic steatosis.

OBJECTIVES: The purpose of this study was to investigate the relation between pancreatic steatosis and visceral adiposity. Furthermore, the study soug...

Alcoholic liver disease: A registry view on comorbidities and disease prediction.

Alcoholic-related liver disease (ALD) is the cause of more than half of all liver-related deaths. Sustained excess drinking causes fatty liver and alc...

Development of a volumetric pancreas segmentation CT dataset for AI applications through trained technologists: a study during the COVID 19 containment phase.

PURPOSE: To evaluate the performance of trained technologists vis-à-vis radiologists for volumetric pancreas segmentation and to assess the impact of ...

Fluence Map Prediction Using Deep Learning Models - Direct Plan Generation for Pancreas Stereotactic Body Radiation Therapy.

Treatment planning for pancreas stereotactic body radiation therapy (SBRT) is a difficult and time-consuming task. In this study, we aim to develop a...

ALICE: a hybrid AI paradigm with enhanced connectivity and cybersecurity for a serendipitous encounter with circulating hybrid cells.

A fully automated and accurate assay of rare cell phenotypes in densely-packed fluorescently-labeled liquid biopsy images remains elusive. Employing ...

Development of a High-Fidelity Robot-Assisted Kidney Transplant Simulation Platform Using Three-Dimensional Printing and Hydrogel Casting Technologies.

Despite the adoption of robotic donor nephrectomy, the steep learning curve of robotic recipient transplantation has hindered the implementation of a...

Pancreatic Cancer Imaging: A New Look at an Old Problem.

Computed tomography is the most commonly used imaging modality to detect and stage pancreatic cancer. Previous advances in pancreatic cancer imaging h...

Characterization of patients with advanced chronic pancreatitis using natural language processing of radiology reports.

STUDY AIM: To develop and apply a natural language processing algorithm for characterization of patients diagnosed with chronic pancreatitis in a dive...

A machine learning approach identified a diagnostic model for pancreatic cancer through using circulating microRNA signatures.

Late diagnosis of pancreatic cancer (PC) due to the limited effectiveness of modern testing approaches, causes many patients to miss the chance of sur...

High spatially sensitive quantitative phase imaging assisted with deep neural network for classification of human spermatozoa under stressed condition.

Sperm cell motility and morphology observed under the bright field microscopy are the only criteria for selecting a particular sperm cell during Intra...

Using machine learning for real-time BAC estimation from a new-generation transdermal biosensor in the laboratory.

BACKGROUND: Transdermal biosensors offer a noninvasive, low-cost technology for the assessment of alcohol consumption with broad potential application...

Modeling motivation for alcohol in humans using traditional and machine learning approaches.

Given the significant cost of alcohol use disorder (AUD), identifying risk factors for alcohol seeking represents a research priority. Prominent addic...