Gastroenterology

Deep causal learning for pancreatic cancer segmentation in CT sequences.

Segmenting the irregular pancreas and inconspicuous tumor simultaneously is an essential but challen...

S2DA-Net: Spatial and spectral-learning double-branch aggregation network for liver tumor segmentation in CT images.

Accurate liver tumor segmentation is crucial for aiding radiologists in hepatocellular carcinoma eva...

A multi-instance tumor subtype classification method for small PET datasets using RA-DL attention module guided deep feature extraction with radiomics features.

BACKGROUND: Positron emission tomography (PET) is extensively employed for diagnosing and staging va...

Cascade-EC Network: Recognition of Gastrointestinal Multiple Lesions Based on EfficientNet and CA_stm_Retinanet.

Capsule endoscopy (CE) is non-invasive and painless during gastrointestinal examination. However, ca...

Therapeutic endoscopy: Recent updates and future directions.

The landscape of therapeutic endoscopy has undergone a remarkable evolution over the past few decade...

Duodenal papilla radiomics-based prediction model for post-ERCP pancreatitis using machine learning: a retrospective multicohort study.

BACKGROUND AND AIMS: The duodenal papillae are the primary and essential pathway for ERCP, greatly d...

Multistep validation of a post-ERCP pancreatitis prediction system integrating multimodal data: a multicenter study.

BACKGROUND AND AIMS: The impact of various categories of information on the prediction of post-ERCP ...

Rapid Endoscopic Diagnosis of Benign Ulcerative Colorectal Diseases With an Artificial Intelligence Contextual Framework.

BACKGROUND & AIMS: Benign ulcerative colorectal diseases (UCDs) such as ulcerative colitis, Crohn's ...

Precise highlighting of the pancreas by semantic segmentation during robot-assisted gastrectomy: visual assistance with artificial intelligence for surgeons.

BACKGROUND: A postoperative pancreatic fistula (POPF) is a critical complication of radical gastrect...

Development and validation of an imageless machine-learning algorithm for the initial screening of prostate cancer.

PURPOSE: Prostate specific antigen (PSA) testing is a low-cost screening method for prostate cancer ...

Automated detection of small bowel lesions based on capsule endoscopy using deep learning algorithm.

BACKGROUND: In order to overcome the challenges of lesion detection in capsule endoscopy (CE), we im...

Deep-learning-based image super-resolution of an end-expandable optical fiber probe for application in esophageal cancer diagnostics.

SIGNIFICANCE: Endoscopic screening for esophageal cancer (EC) may enable early cancer diagnosis and ...

Long-term outcomes of robot-assisted laparoscopic surgery versus conventional laparoscopic surgery for rectal cancer: single-center, retrospective, propensity score analyses.

Although the short-term outcomes of robot-assisted laparoscopic surgery (RALS) for rectal cancer are...

Early gastric cancer detection and lesion segmentation based on deep learning and gastroscopic images.

Gastric cancer is a highly prevalent disease that poses a serious threat to public health. In clinic...

Is the robotic approach the future of distal pancreatectomy with splenectomy? A propensity score matched analysis.

Our study provides a comparative analysis of the Laparo-Endoscopic Single Site (LESS) and robotic su...

Convolutional neural network deep learning model accurately detects rectal cancer in endoanal ultrasounds.

BACKGROUND: Imaging is vital for assessing rectal cancer, with endoanal ultrasound (EAUS) being high...

Artificial Intelligence and Medical Liability in Gastrointestinal Endoscopy.

Deceased-Donor Kidney Transplant Outcome Prediction Using Artificial Intelligence to Aid Decision-Making in Kidney Allocation.

In kidney transplantation, pairing recipients with the highest longevity with low-risk allografts to...

Multi-scale nested UNet with transformer for colorectal polyp segmentation.

BACKGROUND: Polyp detection and localization are essential tasks for colonoscopy. U-shape network ba...

Robustness evaluation of deep neural networks for endoscopic image analysis: Insights and strategies.

Computer-aided detection and diagnosis systems (CADe/CADx) in endoscopy are commonly trained using h...

A natural language processing algorithm accurately classifies steatotic liver disease pathology to estimate the risk of cirrhosis.

BACKGROUND: Histopathology remains the gold standard for diagnosing and staging metabolic dysfunctio...