Peptic Ulcer Disease

Geometric Graph Learning to Predict Changes in Binding Free Energy and Protein Thermodynamic Stability upon Mutation.

Accurate prediction of binding free energy changes upon mutations is vital for optimizing drugs, designing proteins, understanding genetic diseases, and cost-effective virtual screening. While machine learning methods show promise in this domain, achieving accuracy and generalization across diverse data sets remains a challenge. This study introduces Geometric Graph Learning for Protein-Protein In...

Achieving Value by Risk Stratification With Machine Learning Model or Clinical Risk Score in Acute Upper Gastrointestinal Bleeding: A Cost Minimization Analysis.

INTRODUCTION: We estimate the economic impact of applying risk assessment tools to identify very low-risk patients with upper gastrointestinal bleeding who can be safely discharged from the emergency department using a cost minimization analysis.

A Spectrophotometric comparative evaluation of the sealing ability of various perforation repair materials with a novel eggshell modified GIC.

OBJECTIVES: The objective of this study was to evaluate and compare the sealing ability of mineral trioxide aggregate (MTA), Biodentine, glass ionomer...

Co-occurrence of heavy metals and antibiotics resistance in bacteria isolated from metal-polluted soil.

The indiscriminate deposition of metal-containing substances into the environment contributes significantly to high concentrations of metals in the so...

Current trends and future perspectives of stroke management through integrating health care team and nanodrug delivery strategy.

Stroke is accounted as the second-most mortality and adult disability factor in worldwide, while causes the bleeding promptly and lifetime consequence...

Using deep learning to assess the function of gastroesophageal flap valve according to the Hill classification system.

BACKGROUND: The endoscopic Hill classification of the gastroesophageal flap valve (GEFV) is of great importance for understanding the functional statu...

Robot-assisted retroperitoneal lymph node dissection: Initial experience in Japan.

For patients with testicular tumors who need the surgical management, open retroperitoneal lymph node dissection (O-RPLND) is considered the gold stan...

Development of a hybrid hydrogel for submucosal injection in endoscopic resection of gastrointestinal neoplasm: From laboratory to clinical trial.

Submucosal injection solution is essential for successful endoscopic resection of the early gastrointestinal tumor. We evaluated a new endoscopic hyd...

Safety and Effectiveness of an Anti-Xa-based Unfractionated Heparin Protocol for Impella Percutaneous Ventricular Assist Devices.

Impella devices are used for mechanical circulatory support in patients with cardiogenic shock or those undergoing high-risk percutaneous coronary in...

Quantitative image signature and machine learning-based prediction of outcomes in cerebral cavernous malformations.

PURPOSE: There is increasing interest in novel prognostic tools and predictive biomarkers to help identify, with more certainty, cerebral cavernous ma...

Color-coded laparoscopic liver resection using artificial intelligence: A preliminary study.

Tashiro and colleagues demonstrated for the first time that an artificial intelligence system can precisely identify intrahepatic vascular structures ...

Plasma interleukin 6 as an outcome predictor of traumatic brain injury patients.

Traumatic brain injury is one of the leading causes of death and disability in young adults. Previous studies have suggested that neuroinflammatory pr...

Comparison of clinical efficacy of da Vinci robot-assisted lung cancer surgery with two-, three- and four-hole approaches.

Orifice reduction strategies for da Vinci robotic surgery have been a hot topic of research in recent years. We retrospectively analyzed the periopera...

Vocal cord leukoplakia classification using deep learning models in white light and narrow band imaging endoscopy images.

BACKGROUND: Accurate vocal cord leukoplakia classification is critical for the individualized treatment and early detection of laryngeal cancer. Numer...

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 abnormalities from small-bowel capsule endoscopy (SBCE) image...

A multimodal deep learning model for predicting severe hemorrhage in placenta previa.

Placenta previa causes life-threatening bleeding and accurate prediction of severe hemorrhage leads to risk stratification and optimum allocation of i...

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 area of research. Medical science and artificial in...

A real-time deep learning-based system for colorectal polyp size estimation by white-light endoscopy: development and multicenter prospective validation.

BACKGROUND: The choice of polypectomy device and surveillance intervals for colorectal polyps are primarily decided by polyp size. We developed a deep...

Artificial intelligence-based diagnosis of the depth of laryngopharyngeal cancer.

OBJECTIVE: Transoral surgery (TOS) is a widely used treatment for laryngopharyngeal cancer. There are some difficult cases of setting the extent of re...

Deep learning in endoscopy: the importance of standardisation.