Peptic Ulcer Disease

Using protein language models for protein interaction hot spot prediction with limited data.

BACKGROUND: Protein language models, inspired by the success of large language models in deciphering human language, have emerged as powerful tools for unraveling the intricate code of life inscribed within protein sequences. They have gained significant attention for their promising applications across various areas, including the sequence-based prediction of secondary and tertiary protein struct...

Artificial intelligence-assisted assessment for Forrest classification of peptic ulcer bleeding: hype or reality?

Deep learning algorithm for the automated detection and classification of nasal cavity mass in nasal endoscopic images.

Nasal endoscopy is routinely performed to distinguish the pathological types of masses. There is a lack of studies on deep learning algorithms for dis...

Pediatric endoscopy: how can we improve patient outcomes and ensure best practices?

INTRODUCTION: Strategies to promote high-quality endoscopy in children require consensus around pediatric-specific quality standards and indicators. U...

Deciphering the Lexicon of Protein Targets: A Review on Multifaceted Drug Discovery in the Era of Artificial Intelligence.

Understanding protein sequence and structure is essential for understanding protein-protein interactions (PPIs), which are essential for many biologic...

Effects of thienopyridine class antiplatelets on bleeding outcomes following robot-assisted radical prostatectomy.

This study aimed to assess the effects of thienopyridine-class antiplatelet agents (including ticlopidine, clopidogrel, and prasugrel) on bleeding com...

Artificial Intelligence-assisted colonoscopy and colorectal cancer screening: Where are we going?

Colorectal cancer is a significant global health concern, necessitating effective screening strategies to reduce its incidence and mortality rates. Co...

Reassessing acquired neonatal intestinal diseases using unsupervised machine learning.

BACKGROUND: Acquired neonatal intestinal diseases have an array of overlapping presentations and are often labeled under the dichotomous classificatio...

A deep learning model based on magnifying endoscopy with narrow-band imaging to evaluate intestinal metaplasia grading and OLGIM staging: A multicenter study.

BACKGROUND AND PURPOSE: Patients with stage III or IV of operative link for gastric intestinal metaplasia assessment (OLGIM) are at a higher risk of g...

Integrating network pharmacology, molecular docking and simulation approaches with machine learning reveals the multi-target pharmacological mechanism of against diabetic nephropathy.

Diabetic nephropathy (DN) is one of the most feared complications of diabetes and key cause of end-stage renal disease (ESRD). has been widely used t...

Upper gastrointestinal haemorrhage patients' survival: A causal inference and prediction study.

BACKGROUND: Upper gastrointestinal (GI) bleeding is a common medical emergency. This study aimed to develop models to predict critically ill patients ...

Review of robotic surgery platforms and end effectors.

In the last 50 years, the number of companies producing automated devices for surgical operations has grown extensively. The population started to be ...

Retrospective survey of using a novel validated real-time PCR assay.

, an aggressive plant pathogen, causes symptoms on a variety of crops and ornamental plants including bleeding canker of Asian pear trees. Historical ...

Revolutionizing protein-protein interaction prediction with deep learning.

Protein-protein interactions (PPIs) are pivotal for driving diverse biological processes, and any disturbance in these interactions can lead to diseas...

Role of the artificial intelligence in the management of T1 colorectal cancer.

Approximately 10% of submucosal invasive (T1) colorectal cancers demonstrate extraintestinal lymph node metastasis, necessitating surgical interventio...

Editorial comment to Lower bleeding volume contributes to decreasing surgical site infection in radical cystectomy: A propensity score-matched comparison of open versus robot-assisted radical cystectomy.

Use of a Perfused Cadaver for Training of Robotic Pancreaticoduodenectomy Allows for Realistic Tissue Dissection and Management of Intra-Operative Bleeding.

An artificial intelligence system for chronic atrophic gastritis diagnosis and risk stratification under white light endoscopy.

BACKGROUND AND AIMS: The diagnosis and stratification of gastric atrophy (GA) predict patients' gastric cancer progression risk and determine endoscop...

Diagnostic performance of deep-learning-based virtual chromoendoscopy in gastric neoplasms.

BACKGROUNDS: Cycle-consistent generative adversarial network (CycleGAN) is a deep neural network model that performs image-to-image translations. We g...

Bioinformatics and Machine Learning Methods Identified MGST1 and QPCT as Novel Biomarkers for Severe Acute Pancreatitis.

Severe acute pancreatitis (SAP) is a life-threatening gastrointestinal emergency. The study aimed to identify biomarkers and investigate molecular mec...