Peptic Ulcer Disease

Unsupervised machine learning to explore inflammation following cardiopulmonary bypass.

IntroductionCardiac surgery with cardiopulmonary bypass (CPB) often induces systemic inflammatory reaction syndrome (SIRS), affecting postoperative outcome. We aimed to explore adaptive/maladaptive inflammation using unsupervised machine learning.MethodsWe conducted a post hoc analysis of 1908 adult patients who underwent elective cardiac surgery with CPB between June 2016 and June 2020 at a singl...

Screening for Barrett Esophagus and Esophageal Adenocarcinoma: Approaches and Outcomes.

Barrett esophagus (BE) is the only known histological precursor to esophageal adenocarcinoma (EAC). The incidence of EAC has risen significantly over the past 4 decades in the United States and other Western countries, and the prognosis of EAC remains poor, with over half of individuals diagnosed at a late stage. Despite this, fewer than 1 in 5 eligible individuals undergo endoscopic screening for...

Machine Learning in Venous Thromboembolism-Why and What Next?

Venous thromboembolism (VTE) remains a leading cause of cardiovascular morbidity and mortality, despite advances in imaging and anticoagulation. VTE a...

A Review on Efficient and Scalable Graph-Based Clustering Algorithms for Protein Complex Identification in PPI Networks.

Network clustering is employed in bioinformatics and data mining studies to investigate the structural and functional properties of protein-protein in...

A unified graph-based approach for protein function prediction using AlphaFold structures and sequence features.

Predicting protein function is a key challenge in computational biology with broad implications for understanding biological systems and disease mecha...

Chronic Ocular Sequelae of Stevens-Johnson Syndrome: Recent Advances in Understanding of Patho-Physiology and Management.

BACKGROUND: Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are severe mucocutaneous reactions primarily triggered by drugs or inf...

Computer-Aided Diagnosis Using the Large-Scale Visual Language Models in Screening of Digestive Endoscopy.

China's response to the high prevalence of digestive tract diseases involves conducting large-scale endoscopic screening programs. However, the substa...

Graph Neural Networks for Realistic Bleeding Prediction in Surgical Simulators.

This study presents a novel approach using graph neural networks to predict the risk of internal bleeding using vessel maps derived from patient CT an...

Real-time Use of Computer-aided Diagnosis in the Optical Diagnosis of Gastric Neoplasia: A Multicenter Randomized Controlled Trial.

BACKGROUND & AIMS: The multicenter, randomized, control trial was conducted to evaluate whether computer-aided diagnosis (CADx) improves the optical d...

Can a Rule-Based Expert System Diagnose Nasal Obstruction from Nasoendoscopy Videos?

Nasal obstruction has multiple causes requiring specialist endoscopy for diagnosis. A rule-based expert system (RB-ES), which applies five "if-then" r...

A comprehensive analysis of transcription factors identified TCF3 as a prognostic target for glioma.

Transcription factors (TFs) are pivotal in tumor initiation and progression, regulating downstream gene expression and modulating cellular processes. ...

Prediction of gastrointestinal hemorrhage in cardiology inpatients using an interpretable XGBoost model.

Gastrointestinal bleeding (GIB) occurs more frequently in cardiovascular patients than in the general population, significantly affecting morbidity an...

Development and validation of a machine learning-based nomogram for survival prediction of patients with hilar cholangiocarcinoma after curative-intent resection.

Hilar cholangiocarcinoma (hCCA), a rare cancer of the biliary system, has a poor prognosis. This study aimed to investigate the risk factors affecting...

Analysis of Protein-Protein Interactions in CC125 by Co-Fractionation Mass Spectrometry.

, a unicellular eukaryotic green alga, is an important biological model. Previous studies on protein complexes in have primarily focused on photosynt...

Autoimmune gastritis detection from preprocessed endoscopy images using deep transfer learning and moth flame optimization.

Gastric Tract Disease (GTD) constitutes a medical emergency, emphasizing the critical importance of early diagnosis and intervention to lessen its sev...

How machine learning on real world clinical data improves adverse event recording for endoscopy.

Endoscopic interventions are essential for diagnosing and treating gastrointestinal conditions. Accurate and comprehensive documentation is crucial fo...

Recent advancement in endoscopic diagnosis for risk stratification of gastric cancer.

Approximately 90% of cases of gastric cancer (GC) are caused by Helicobacter pylori infection, and screening esophagogastroduodenoscopy is effective f...

Advantages and effectiveness of AI three-dimensional reconstruction technology in the preoperative planning of total hip arthroplasty.

In order to explore the application effect of artificial intelligence (AI) 3D reconstruction technology in total hip arthroplasty (THA), this study in...

Deep learning-based allergic rhinitis diagnosis using nasal endoscopy images.

Allergic rhinitis typically has edematous and pale turbinates or erythematous and inflamed turbinates. While traditional approaches include using skin...

Prediction model of recurrence in patients with lumbar disc herniation after unilateral biportal endoscopy spinal surgery- XGBoost machine learning model can be interpreted based on SHAP.