Gastroenterology

Back Propagation Neural Network-Based Magnetic Resonance Imaging Image Features in Treating Intestinal Obstruction in Digestive Tract Diseases with Chengqi Decoction.

This study was to explore the adoption effect of magnetic resonance imaging (MRI) image features based on back propagation neural network (BPNN) in evaluating the curative effect of Chengqi Decoction (CD) for intestinal obstruction (ileus), so as to evaluate the clinical adoption value of this algorithm. Ninety patients with ileus were recruited, and the patients were treated with CD and underwent...

Essential updates 2020/2021: Current topics of simulation and navigation in hepatectomy.

With the development of three-dimensional (3D) simulation software, preoperative simulation technology is almost completely established. The remaining issue is how to recognize anatomy three-dimensionally. Extended reality is a newly developed technology with several merits for surgical application: no requirement for a sterilized display monitor, better spatial awareness, and the ability to share...

Deep Learning in the Classification of Stage of Liver Fibrosis in Chronic Hepatitis B with Magnetic Resonance ADC Images.

Liver fibrosis in chronic hepatitis B is the pathological repair response of the liver to chronic injury, which is a key step in the development of va...

Outcomes of Robot-Assisted Laparoscopic Isthmus Division Using Endoscopic Transection Equipment in the Treatment of Symptomatic Horseshoe Kidney.

The surgical treatment of horseshoe kidney (HSK) remains a huge challenge because of the complex anatomy and abnormal blood vessel distribution. Ther...

Artificial Neural Network Analysis-Based Immune-Related Signatures of Primary Non-Response to Infliximab in Patients With Ulcerative Colitis.

Infliximab (IFX) is an effective medication for ulcerative colitis (UC) patients. However, one-third of UC patients show primary non-response (PNR) to...

Introducing robot-assisted laparoscopic donor nephrectomy after experience in retroperitoneal endoscopic approach: a matched propensity score analysis.

OBJECTIVES: To assess the safety and efficacy of introducing robotic-assisted laparoscopic donor nephrectomy (RALDN) to the standard retroperitoneal e...

Deep Learning and Device-Assisted Enteroscopy: Automatic Detection of Gastrointestinal Angioectasia.

: Device-assisted enteroscopy (DAE) allows deep exploration of the small bowel and combines diagnostic and therapeutic capacities. Suspected mid-gastr...

Multi-scale Selection and Multi-channel Fusion Model for Pancreas Segmentation Using Adversarial Deep Convolutional Nets.

Organ segmentation from existing imaging is vital to the medical image analysis and disease diagnosis. However, the boundary shapes and area sizes of ...

Identification of Barrett's esophagus in endoscopic images using deep learning.

BACKGROUND: Development of a deep learning method to identify Barrett's esophagus (BE) scopes in endoscopic images.

Effects of nano-manganese on humoral immune response and oxidative stress in broilers.

The objective of the present study was to evaluate the alterations in selected indicators of immune responses and oxidative stress of broilers fed wit...

Robotic Versus Laparoscopic Surgery for Rectal Cancer: A Comprehensive Review of Oncological Outcomes.

The treatment of rectal cancer is complex and involves specialized multidisciplinary care, although the tenet is still rooted in a high-quality total ...

Deciphering tumour tissue organization by 3D electron microscopy and machine learning.

Despite recent progress in the characterization of tumour components, the tri-dimensional (3D) organization of this pathological tissue and the parame...

Predictive Model for Drug-Induced Liver Injury Using Deep Neural Networks Based on Substructure Space.

Drug-induced liver injury (DILI) is a major concern for drug developers, regulators, and clinicians. However, there is no adequate model system to ass...

Artificial Intelligence and Deep Learning for Upper Gastrointestinal Neoplasia.

Upper gastrointestinal (GI) neoplasia account for 35% of GI cancers and 1.5 million cancer-related deaths every year. Despite its efficacy in preventi...

QSAR and deep learning model for virtual screening of potential inhibitors against Inosine 5' Monophosphate dehydrogenase (IMPDH) of Cryptosporidium parvum.

Cryptosporidium parvum (Cp) causes a gastro-intestinal disease called Cryptosporidiosis. C. parvum Inosine 5' monophosphate dehydrogenase (CpIMPDH) is...

Artificial intelligence and inflammatory bowel disease: practicalities and future prospects.

Artificial intelligence (AI) is an emerging technology predicted to have significant applications in healthcare. This review highlights AI application...

Diagnosing the Stage of Hepatitis C Using Machine Learning.

Hepatitis C is a prevalent disease in the world. Around 3 to 4 million new cases of Hepatitis C are reported every year across the globe. Effective, t...

Artificial intelligence for the assessment of bowel preparation.

BACKGROUND AND AIMS: A reliable assessment of bowel preparation is important to ensure high-quality colonoscopy. Current bowel preparation scoring sys...

Identifying Microbe-Disease Association Based on a Novel Back-Propagation Neural Network Model.

Over the years, numerous evidences have demonstrated that microbes living in the human body are closely related to human life activities and human dis...

Optimizing hepatitis B virus screening in the United States using a simple demographics-based model.

BACKGROUND AND AIMS: Chronic hepatitis B (CHB) affects >290 million persons globally, and only 10% have been diagnosed, presenting a severe gap that m...