Gastroenterology

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...

Deep learning in endoscopy: the importance of standardisation.

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...

Reply: ChatGPT and unknown clinical questions about liver transplantation.

Letter to the Editor: ChatGPT and unknown clinical questions about liver transplantation.

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...

Short- and long-term outcomes of robot-assisted versus thoracoscopy-assisted minimally invasive esophagectomy.

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...

Tumor classification of gastrointestinal liver metastases using CT-based radiomics and deep learning.

OBJECTIVES: The goal of this study is to demonstrate the performance of radiomics and CNN-based clas...

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...

Construction of Immune Infiltration-Related LncRNA Signatures Based on Machine Learning for the Prognosis in Colon Cancer.

Colon cancer is one of the malignant tumors with high morbidity, lethality, and prevalence across gl...

Long-term Outcomes of Robot-assisted Versus Laparoscopic Surgery for Colon Cancer: A Nationwide Register-based Cohort Study.

OBJECTIVE: To determine long-term survival in patients undergoing robot-assisted surgery (RAS) or la...

A deep learning model to triage and predict adenocarcinoma on pancreas cytology whole slide imaging.

Pancreatic fine-needle aspirations are the gold-standard diagnostic procedure for the evaluation of ...

Investigating Transformer Encoding Techniques to Improve Data-Driven Volume-to-Surface Liver Registration for Image-Guided Navigation.

Due to limited direct organ visualization, minimally invasive interventions rely extensively on medi...

The Use of Artificial Intelligence in Gastroenterology: A Glimpse Into the Present.

Using Artificial Intelligence to Predict Cirrhosis From Computed Tomography Scans.

INTRODUCTION: Undiagnosed cirrhosis remains a significant problem. In this study, we developed and t...

Deep Learning and Minimally Invasive Endoscopy: Automatic Classification of Pleomorphic Gastric Lesions in Capsule Endoscopy.

INTRODUCTION: Capsule endoscopy (CE) is a minimally invasive examination for evaluating the gastroin...

A commentary on 'Advances in artificial intelligence (AI) based diagnosis and treatment of liver diseases - correspondence'.