Pancreatic Diseases

A deep learning detection method for pancreatic cystic neoplasm based on Mamba architecture.

OBJECTIVE: Early diagnosis of pancreatic cystic neoplasm (PCN) is crucial for patient survival. This study proposes M-YOLO, a novel model combining Mamba architecture and YOLO, to enhance the detection of pancreatic cystic tumors. The model addresses the technical challenge posed by the tumors' complex morphological features in medical images.

Neural Network-Assisted Dual-Functional Hydrogel-Based Microfluidic SERS Sensing for Divisional Recognition of Multimolecule Fingerprint.

To enhance the sensitivity, integration, and practicality of the Raman detection system, a deep learning-based dual-functional subregional microfluidic integrated hydrogel surface-enhanced Raman scattering (SERS) platform is proposed in this paper. First, silver nanoparticles (Ag NPs) with a homogeneous morphology were synthesized using a one-step reduction method. Second, these Ag NPs were embedd...

Machine learning via DARTS-Optimized MobileViT models for pancreatic Cancer diagnosis with graph-based deep learning.

The diagnosis of pancreatic cancer presents a significant challenge due to the asymptomatic nature of the disease and the fact that it is frequently d...

Triboelectric Sensors Based on Glycerol/PVA Hydrogel and Deep Learning Algorithms for Neck Movement Monitoring.

Prolonged use of digital devices and sedentary lifestyles have led to an increase in the prevalence of cervical spondylosis among young people, highli...

Functionally characterizing obesity-susceptibility genes using CRISPR/Cas9, in vivo imaging and deep learning.

Hundreds of loci have been robustly associated with obesity-related traits, but functional characterization of candidate genes remains a bottleneck. A...

Deep learning-based quick MLC sequencing for MRI-guided online adaptive radiotherapy: a feasibility study for pancreatic cancer patients.

One bottleneck of magnetic resonance imaging (MRI)-guided online adaptive radiotherapy is the time-consuming daily online replanning process. The curr...

Biopsychosocial based machine learning models predict patient improvement after total knee arthroplasty.

Total knee arthroplasty (TKA) is an effective treatment for end stage osteoarthritis. However, biopsychosocial features are not routinely considered i...

A deep learning-driven method for safe and effective ERCP cannulation.

PURPOSE: In recent years, the detection of the duodenal papilla and surgical cannula has become a critical task in computer-assisted endoscopic retrog...

Deep learning radiomics nomogram for preoperatively identifying moderate-to-severe chronic cholangitis in children with pancreaticobiliary maljunction: a multicenter study.

BACKGROUND: Long-term severe cholangitis can lead to dense adhesions and increased fragility of the bile duct, complicating surgical procedures and el...

Multiscale deep learning radiomics for predicting recurrence-free survival in pancreatic cancer: A multicenter study.

PURPOSE: This multicenter study aimed to develop and validate a multiscale deep learning radiomics nomogram for predicting recurrence-free survival (R...

Super-resolution deep-learning reconstruction with 1024 matrix improves CT image quality for pancreatic ductal adenocarcinoma assessment.

OBJECTIVES: To evaluate the efficiency of super-resolution deep-learning reconstruction (SR-DLR) optimized for helical body imaging in assessing pancr...

K-nearest neighbor algorithm for imputing missing longitudinal prenatal alcohol data.

AIMS: The objective of this study is to illustrate the application of a machine learning algorithm, K Nearest Neighbor () to impute missing alcohol da...

An endoscopic ultrasound-based interpretable deep learning model and nomogram for distinguishing pancreatic neuroendocrine tumors from pancreatic cancer.

To retrospectively develop and validate an interpretable deep learning model and nomogram utilizing endoscopic ultrasound (EUS) images to predict panc...

A safe-enhanced fully closed-loop artificial pancreas controller based on deep reinforcement learning.

Patients with type 1 diabetes and their physicians have long desired a fully closed-loop artificial pancreas (AP) system that can alleviate the burden...

Artificial Intelligence in Pancreatic Imaging: A Systematic Review.

The rising incidence of pancreatic diseases, including acute and chronic pancreatitis and various pancreatic neoplasms, poses a significant global hea...

Deep Learning Enabled Scoring of Pancreatic Neuroendocrine Tumors Based on Cancer Infiltration Patterns.

Pancreatic neuroendocrine tumors (PanNETs) are a heterogeneous group of neoplasms that include tumors with different histomorphologic characteristics ...

A comparative analysis and survival analysis of open versus minimally invasive radical antegrade modular pancreatosplenectomy for pancreatic cancer: a systematic review and meta-analysis.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a major public health concern, ranking as the fourth leading cause of cancer-related mortality ...

Machine learning algorithms for predicting PTSD: a systematic review and meta-analysis.

This study aimed to compare and evaluate the prediction accuracy and risk of bias (ROB) of post-traumatic stress disorder (PTSD) predictive models. We...

Motion-Compensated Multishot Pancreatic Diffusion-Weighted Imaging With Deep Learning-Based Denoising.

OBJECTIVES: Pancreatic diffusion-weighted imaging (DWI) has numerous clinical applications, but conventional single-shot methods suffer from off reson...

Deep learning-based MVIT-MLKA model for accurate classification of pancreatic lesions: a multicenter retrospective cohort study.

BACKGROUND: Accurate differentiation between benign and malignant pancreatic lesions is critical for effective patient management. This study aimed to...