A5094358759- Cardiovascular Function and Risk Factors
- Diabetes, Cardiovascular Risks, and Lipoproteins
- Artificial Intelligence in Healthcare
- Gastrointestinal Bleeding Diagnosis and Treatment
- Heart Failure Treatment and Management
- Cardiac Imaging and Diagnostics
- Gastric Cancer Management and Outcomes
Specialty Hospital, Jordan
2024
Hashemite University
2024
This study aimed to introduce a novel machine learning (ML) model designed predict the need of interventions during endoscopy in patients with upper gastrointestinal bleeding (UGIB). The risk stratification tools current use, such as Glasgow Blatchford Score (GBS) and pre-endoscopic Rockall score, have limitations accurately predicting for endoscopic interventions. All diagnosed UGIB from January 2013 October 2023 who underwent were included study. Variables extracted demographics, social...
Background: Heart failure (HF) is a common final pathway of various insults to the heart, primarily from risk factors including diabetes mellitus (DM) type 2. This study analyzed clinical characteristics HF in Jordanian population with particular emphasis on relationship between DM and HF. Methods: prospective used Failure Registry (JoHFR) data. Patients were characterized by status type: preserved ejection fraction (HFpEF) or reduced (HFrEF). Demographics, presentations, treatment outcomes...
Background: Heart failure (HF) is a global health challenge affecting millions, with significant variations in patient characteristics and outcomes based on ejection fraction. This study aimed to differentiate between HF reduced fraction (HFrEF) preserved (HFpEF) respect characteristics, risk factors, comorbidities, clinical outcomes, incorporating advanced machine learning models for mortality prediction. Methodology: The included 1861 patients from 21 centers Jordan, categorized into HFrEF...