Gastroenterology

Accurate Liver Fibrosis Detection Through Hybrid MRMR-BiLSTM-CNN Architecture with Histogram Equalization and Optimization.

The early detection and accurate diagnosis of liver fibrosis, a progressive and potentially serious liver condition, are crucial for effective medical intervention. Invasive methods like biopsies for diagnosis can be risky and expensive. This research presents a novel computer-aided diagnosis model for liver fibrosis using a hybrid approach of minimum redundancy maximum relevance (MRMR) feature se...

A machine-learning model based on dynamic contrast-enhanced MRI for preoperative differentiation between hepatocellular carcinoma and combined hepatocellular-cholangiocarcinoma.

AIM: To establish a machine-learning model based on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) to differentiate combined hepatocellular-cholangiocarcinoma (cHCC-CC) from hepatocellular carcinoma (HCC) before surgery.

Experts vs. machine - comparison of machine learning to expert-informed prediction of outcome after major liver surgery.

BACKGROUND: Machine learning (ML) has been successfully implemented for classification tasks (e.g., cancer diagnosis). ML performance for more challen...

nnU-Net-Based Pancreas Segmentation and Volume Measurement on CT Imaging in Patients with Pancreatic Cancer.

RATIONALE AND OBJECTIVES: To develop and validate a deep learning (DL)-based method for pancreas segmentation on CT and automatic measurement of pancr...

Replication and Injury Associated With SARS-CoV-2 in Cultured Hepatocytes.

BACKGROUND: Liver dysfunction is one of the hallmarks of SARS-CoV-2 infection. The mechanism(s) of hepatic injury in SARS-CoV-2 infection remains cont...

NAIF: A novel artificial intelligence-based tool for accurate diagnosis of stage F3/F4 liver fibrosis in the general adult population, validated with three external datasets.

OBJECTIVE: The purpose of this study was to determine the effectiveness of a new AI-based tool called NAIF (NAFLD-AI-Fibrosis) in identifying individu...

Deep learning model to differentiate Crohn's disease from intestinal tuberculosis using histopathological whole slide images from intestinal specimens.

Crohn's disease (CD) and intestinal tuberculosis (ITB) share similar histopathological characteristics, and differential diagnosis can be a dilemma fo...

Classification of H. pylori Infection from Histopathological Images Using Deep Learning.

Helicobacter pylori (H. pylori) is a widespread pathogenic bacterium, impacting over 4 billion individuals globally. It is primarily linked to gastric...

First clinical experiences of robotic gastrectomy for gastric cancer using the hinotori™ surgical robot system.

BACKGROUND: Although the da Vinci™ Surgical System is the most predominantly used surgical robot worldwide, other surgical robots are being developed....

Robotic surgery for bowel endometriosis: a multidisciplinary management of a complex entity.

BACKGROUND: Bowel endometriosis impacts quality of life. Treatment requires complex surgical procedures with associated morbidity. Precision approach ...

Autonomous Artificial Intelligence vs Artificial Intelligence-Assisted Human Optical Diagnosis of Colorectal Polyps: A Randomized Controlled Trial.

BACKGROUND & AIMS: Artificial intelligence (AI)-based optical diagnosis systems (CADx) have been developed to allow pathology prediction of colorectal...

A multicenter clinical AI system study for detection and diagnosis of focal liver lesions.

Early and accurate diagnosis of focal liver lesions is crucial for effective treatment and prognosis. We developed and validated a fully automated dia...

Application of Machine Learning Techniques to Assess Alpha-Fetoprotein at Diagnosis of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the most common primary liver tumor and is associated with high mortality rates. Approximately 80% of cases occur in...

Oral_voting_transfer: classification of oral microorganisms' function proteins with voting transfer model.

INTRODUCTION: The oral microbial group typically represents the human body's highly complex microbial group ecosystem. Oral microorganisms take part i...

Robot-assisted transcervical esophagectomy with a bilateral cervical approach for thoracic esophagectomy.

BACKGROUND: Thoracic esophageal cancer resection through the neck approach has recently been reported as mediastinoscopic surgery. We present the firs...

Predicting malnutrition in gastric cancer patients using computed tomography(CT) deep learning features and clinical data.

OBJECTIVE: The aim of this study is using clinical factors and non-enhanced computed tomography (CT) deep features of the psoas muscles at third lumba...

Donor hepatitis C status is not associated with an increased risk of acute rejection in kidney transplantation.

INTRODUCTION: In renal transplantation, donor hepatitis C virus (HCV) status is crucial to consider when selecting a recipient given the high likeliho...

Explainable artificial intelligence prediction-based model in laparoscopic liver surgery for segments 7 and 8: an international multicenter study.

BACKGROUND: Artificial intelligence (AI) is becoming more useful as a decision-making and outcomes predictor tool. We have developed AI models to pred...

Machine Learning Predicts Oxaliplatin Benefit in Early Colon Cancer.

PURPOSE: A combination of fluorouracil, leucovorin, and oxaliplatin (FOLFOX) is the standard for adjuvant therapy of resected early-stage colon cancer...

Interactive content-based image retrieval with deep learning for CT abdominal organ recognition.

Recognizing the most relevant seven organs in an abdominal computed tomography (CT) slice requires sophisticated knowledge. This study proposed automa...