A5014675429- Pancreatitis Pathology and Treatment
- Gastrointestinal Bleeding Diagnosis and Treatment
- Gallbladder and Bile Duct Disorders
- Pancreatic and Hepatic Oncology Research
- Esophageal and GI Pathology
- Gastrointestinal disorders and treatments
- Pediatric Hepatobiliary Diseases and Treatments
- Vascular Malformations and Hemangiomas
- Neuroendocrine Tumor Research Advances
- Appendicitis Diagnosis and Management
- Bone and Joint Diseases
- Lung Cancer Research Studies
- Systemic Sclerosis and Related Diseases
- Helicobacter pylori-related gastroenterology studies
- FinTech, Crowdfunding, Digital Finance
- Dental Radiography and Imaging
- Hemoglobinopathies and Related Disorders
- Cardiovascular Issues in Pregnancy
- Hepatocellular Carcinoma Treatment and Prognosis
- Blood transfusion and management
- Kawasaki Disease and Coronary Complications
- Dermatologic Treatments and Research
- Mast cells and histamine
- Coronary Artery Anomalies
- Iron Metabolism and Disorders
Semmelweis University
2023-2025
University of Bologna
2025
University of Pecs
2022
Hospital Universitario Fundación Alcorcón
2017
Abstract Rapid and accurate identification of high-risk acute gastrointestinal bleeding (GIB) patients is essential. We developed two machine-learning (ML) models to calculate the risk in-hospital mortality in admitted due overt GIB. analyzed prospective, multicenter Hungarian GIB Registry’s data. The predictive performance XGBoost CatBoost algorithms with Glasgow-Blatchford (GBS), pre-endoscopic Rockall ABC scores were compared. evaluated our using five-fold cross-validation, was measured...
<title>Abstract</title> <bold>Purpose: </bold>Kawasaki disease (KD) can be complicated, mainly during the acute stage, by coronary artery lesions (CALs); their persistence, after subacute increases cardiovascular morbidity and life-threatening events lifelong. While several scores, based on Asians Americans, have been proposed to predict risk of CALs or non-response, less efforts aimed identify factors associated with persistence (pCALs). Our study aimed, firstly, for pCALs in Italian...
<title>Abstract</title> Rapid and accurate identification of high-risk acute gastrointestinal bleeding (GIB) patients is essential. We developed two machine-learning (ML) models to calculate the risk in-hospital mortality in admitted due overt GIB. analyzed prospective, multicenter Hungarian GIB Registry's data. The predictive performance XGBoost CatBoost algorithms with Glasgow-Blatchford (GBS) pre-endoscopic Rockall scores were compared. evaluated our using five-fold cross-validation, was...
Abstract Patients with gastrointestinal bleeding (GIB) exhibit varying tolerances to acute blood loss. We aimed investigate the effect of relative Hb decrease (ΔHb%) on GIB outcomes. Participants enrolled in Hungarian Registry between 2019 and 2022 were analyzed. The primary outcome, defined as a composite endpoint, included in-hospital bleeding-related mortality need for urgent intervention. Four groups created based lowest measured during hospitalization (nadirHb), along four subgroups...