Gastroenterology

The Role of Artificial Intelligence and Texture Analysis in Interventional Radiological Treatments of Liver Masses: A Narrative Review.

Liver lesions, including both benign and malignant tumors, pose significant challenges in interventional radiological treatment planning and prognostication. The emerging field of artificial intelligence (AI) and its integration with texture analysis techniques have shown promising potential in predicting treatment outcomes, enhancing precision, and aiding clinical decision-making. This comprehens...

The effect of the re-segmentation method on improving the performance of rectal cancer image segmentation models.

BACKGROUND: Rapid and accurate segmentation of tumor regions from rectal cancer images can better understand the patientâs lesions and surrounding tissues, providing more effective auxiliary diagnostic information. However, cutting rectal tumors with deep learning still cannot be compared with manual segmentation, and a major obstacle to cutting rectal tumors with deep learning is the lack of high...

A deep learning approach for acute liver failure prediction with combined fully connected and convolutional neural networks.

BACKGROUND: Acute Liver Failure (ALF) is a critical medical condition with rapid development, often caused by viral infections, hepatotoxic drug abuse...

A Preoperative Prediction Model for Lymph Node Metastasis in Patients with Gastric Cancer Using a Machine Learning-based Ultrasomics Approach.

OBJECTIVE: This study aimed to develop an ultrasomics model for predicting lymph node metastasis preoperative in patients with gastric cancer (GC).

A Dynamic Context Encoder Network for Liver Tumor Segmentation.

BACKGROUND: Accurate segmentation of liver tumor regions in medical images is of great significance for clinical diagnosis and the planning of surgica...

Evaluation of Neoadjuvant Chemoradiotherapy Response in Rectal Cancer Using MR Images and Deep Learning Neural Networks.

INTRODUCTION: The aim of the study was to develop deep-learning neural networks to guide treatment decisions and for the accurate evaluation of tumor ...

Fuzzy-Based Bioengineering System for Predicting and Diagnosing Diseases of the Nervous System Triggered by the Interaction of Industrial Frequency Electromagnetic Fields.

The study aims to enhance the standard of medical care for individuals working in the electric power industry who are exposed to industrial frequency ...

Gastrointestinal tract disease detection via deep learning based structural and statistical features optimized hexa-classification model.

BACKGROUND: Gastrointestinal tract (GIT) diseases impact the entire digestive system, spanning from the mouth to the anus. Wireless Capsule Endoscopy ...

Machine Learning Identify Ferroptosis-Related Genes as Potential Diagnostic Biomarkers for Gastric Intestinal Metaplasia.

BACKGROUND: Gastric intestinal metaplasia(GIM) is an independent risk factor for GC, however, its pathogenesis is still unclear. Ferroptosis is a new ...

Machine learning identifies a 5-serum cytokine panel for the early detection of chronic atrophy gastritis patients.

BACKGROUND: Chronic atrophy gastritis (CAG) is a high-risk pre-cancerous lesion for gastric cancer (GC). The early and accurate detection and discrimi...

A Hybrid 2D Gaussian Filter and Deep Learning Approach with Visualization of Class Activation for Automatic Lung and Colon Cancer Diagnosis.

Cancer is a significant public health issue due to its high prevalence and lethality, particularly lung and colon cancers, which account for over a qu...

Prediction of T Stage of Rectal Cancer After Neoadjuvant Therapy by Multi-Parameter Magnetic Resonance Radiomics Based on Machine Learning Algorithms.

INTRODUCTION: Since the response of patients with rectal cancer (RC) to neoadjuvant therapy is highly variable, there is an urgent need to develop acc...

Deep Learning-based U-Mamba Model to Predict Differentiated Gastric Cancer using Radiomics Features from Spleen Segmentation.

OBJECTIVE: This study aimed to develop an automated method for segmenting spleen computed tomography (CT) images using a deep learning model to addres...

Real-World Screening Data for Liver Fibrosis in Psoriasis Patients Treated with Biologics.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is positively associated with the prevalence and severity of psoriasis. T...

Challenges involved in the application of artificial intelligence in gastroenterology: The race is on!

Gastroenterology is a particularly data-rich field, generating vast repositories of data that are a fruitful ground for artificial intelligence (AI) a...

Development and evaluation of acceptance scale for artificial intelligence in digestive endoscopy by subjects.

OBJECTIVES: Digestive endoscopy is an important diagnostic and therapeutic tool for digestive system diseases. The artificial intelligence (AI)-assist...

[A study of the clinical curative effect of nucleos(t)ide analogues treated to pegylated interferon-α add-on therapy in patients with chronic hepatitis B].

To investigate the hepatitis B surface antigen (HBsAg) clearance condition and its predictive factors after treatment with nucleos(t)ide analogues to...

[Robot Assisted Para-Aortic Lymphadenectomy in Gastric Cancer Surgery].

Para-aortic lymphadenectomy in gastric cancer surgery is a highly difficult surgical technique. In our hospital, we introduced robotic surgery in anti...

[A Case of Robot-Assisted Laparoscopic Surgery for Stenotic Sigmoid Colon Cancer with Simultaneous Lateral Lymph Node Metastasis].

The patient is a 63-year-old man. He visited his previous physician for abdominal pain. After close examinations, he was diagnosed with stenotic sigmo...

[Gentle Method to Elevate Left Liver Lobe in Robot Assisted Gastrectomy].

Robot-assisted gastrectomy with the Davinci XiTM has been performed in our department since August 2019. This technique requires elevation of the left...