Gastroenterology

Estimation of right lobe graft weight for living donor liver transplantation using deep learning-based fully automatic computed tomographic volumetry.

This study aimed at developing a fully automatic technique for right lobe graft weight estimation us...

Randomized controlled phase III trial to investigate superiority of robot-assisted gastrectomy over laparoscopic gastrectomy for clinical stage T1-4aN0-3 gastric cancer patients (JCOG1907, MONA LISA study): a study protocol.

BACKGROUND: Laparoscopic gastrectomy (LG) is considered a standard treatment for clinical stage I ga...

A Comparison of Endoscope-Assisted and Open Frontoorbital Distraction for the Treatment of Unicoronal Craniosynostosis.

BACKGROUND: Frontoorbital distraction osteogenesis (FODO) is an established surgical technique for p...

Anaphylactic Shock to Intravenous Indocyanine Green During a Robotic Right Colectomy.

Intravenous indocyanine green (IV ICG) is regarded as a safe immunofluorescence agent used to assess...

Application of multiple-finding segmentation utilizing Mask R-CNN-based deep learning in a rat model of drug-induced liver injury.

Drug-induced liver injury (DILI) presents significant diagnostic challenges, and recently artificial...

Leveraging telemedicine in gastroenterology and hepatology: a narrative review.

BACKGROUND AND OBJECTIVE: Over the years, telemedicine has played a prominent role in delivering hea...

Robotic en bloc resection for T4 left-sided colon cancer-A video vignette.

Unraveling the complexities of pathological voice through saliency analysis.

The human voice is an essential communication tool, but various disorders and habits can disrupt it....

Comparison of clinical utility of deep learning-based systems for small-bowel capsule endoscopy reading.

BACKGROUND AND AIM: Convolutional neural network (CNN) systems that automatically detect abnormaliti...

Clinical feasibility of deep learning reconstruction in liver diffusion-weighted imaging: Improvement of image quality and impact on apparent diffusion coefficient value.

PURPOSE: Diffusion-weighted imaging (DWI) of the liver suffers from low resolution, noise, and artif...

Gastrointestinal tract disorders classification using ensemble of InceptionNet and proposed GITNet based deep feature with ant colony optimization.

Computer-aided classification of diseases of the gastrointestinal tract (GIT) has become a crucial a...

Polygenic modelling and machine learning approaches in pharmacogenomics: Importance in downstream analysis of genome-wide association study data.

Genome-wide association studies (GWAS) have identified genetic variations associated with adverse dr...

Artificial intelligence quantifying endoscopic severity of ulcerative colitis in gradation scale.

OBJECTIVES: Existing endoscopic scores for ulcerative colitis (UC) objectively categorize disease se...

Identifying primary tumor site of origin for liver metastases via a combination of handcrafted and deep learning features.

Liver is one of the most common sites for metastases, which can occur on account of primary tumors f...

Outcomes of totally robotic Roux-en-Y gastric bypass in patients with BMI ≥ 50 kg/m: can the robot level out "traditional" risk factors?

Roux-en-Y gastric bypass (RYGB) in patients with body mass index (BMI) ≥ 50 kg/m is a challenging pr...

Analysis of clinical efficacy and safety of hand-sewn anastomosis for the digestive tract with Da Vinci robot in rectal cancer surgery.

PURPOSE: The study aimed to analyze the clinical efficacy and safety of hand-sewn anastomosis for th...

Prediction of Five-Year Survival Rate for Rectal Cancer Using Markov Models of Convolutional Features of RhoB Expression on Tissue Microarray.

The ability to predict survival in cancer is clinically important because the finding can help patie...

Deep learning enables the discovery of a novel cuproptosis-inducing molecule for the inhibition of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common and deadly cancers in the world. The therap...

A multitask deep learning radiomics model for predicting the macrotrabecular-massive subtype and prognosis of hepatocellular carcinoma after hepatic arterial infusion chemotherapy.

BACKGROUND: The macrotrabecular-massive (MTM) is a special subtype of hepatocellular carcinoma (HCC)...

Towards deep-learning (DL) based fully automated target delineation for rectal cancer neoadjuvant radiotherapy using a divide-and-conquer strategy: a study with multicenter blind and randomized validation.

PURPOSE: Manual clinical target volume (CTV) and gross tumor volume (GTV) delineation for rectal can...

Dimensionality reduction for deep learning in infrared microscopy: a comparative computational survey.

While infrared microscopy provides molecular information at spatial resolution in a label-free manne...