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Predictive model of in-hospital mortality in liver cirrhosis patients with hyponatremia: an artificial neural network approach.
Scientific reports
Nov 20, 2024
Hyponatremia can worsen the outcomes of patients with liver cirrhosis. However, it remains unclear about how to predict the risk of death in cirrhotic patients with hyponatremia. Patients with liver cirrhosis and hyponatremia were screened. Eligible ...
Machine learning-based prediction of elevated N terminal pro brain natriuretic peptide among US general population.
ESC heart failure
Nov 19, 2024
AIMS: Natriuretic peptide-based pre-heart failure screening has been proposed in recent guidelines. However, an effective strategy to identify screening targets from the general population, more than half of which are at risk for heart failure or pre...
Using machine learning to identify pediatric ophthalmologists.
Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus
Nov 19, 2024
This cross-sectional study used data from the American Academy of Ophthalmology IRIS Registry (Intelligent Research in Sight) and machine learning algorithms to identify pediatric ophthalmologists based on physician coding patterns. A random forest m...
Machine learning outperforms the Canadian Triage and Acuity Scale (CTAS) in predicting need for early critical care.
CJEM
Nov 19, 2024
STUDY OBJECTIVE: This study investigates the potential to improve emergency department (ED) triage using machine learning models by comparing their predictive performance with the Canadian Triage Acuity Scale (CTAS) in identifying the need for critic...
Development of machine learning models for predicting depressive symptoms in knee osteoarthritis patients.
Scientific reports
Nov 19, 2024
Knee osteoarthritis (KOA) combined with depressive symptoms is prevalent and leads to poor outcomes and significant financial burdens. However, practical tools for identifying at-risk patients remain limited. A robust prediction model is needed to ad...
Machine learning model-based preterm birth prediction and clinical nomogram: A big retrospective cohort study.
International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Nov 18, 2024
OBJECTIVE: This study sought to develop a multifactorial predictive model for preterm birth risk, with the goal of providing clinical practitioners with early prevention.
Comparative efficacy of anteroposterior and lateral X-ray based deep learning in the detection of osteoporotic vertebral compression fracture.
Scientific reports
Nov 18, 2024
Magnetic resonance imaging remains the gold standard for diagnosing osteoporotic vertebral compression fractures (OVCF), but the use of X-ray imaging, particularly anteroposterior (AP) and lateral views, is prevalent due to its accessibility and cost...
Application of Machine Learning to Osteoporosis and Osteopenia Screening Using Hand Radiographs.
The Journal of hand surgery
Nov 16, 2024
PURPOSE: Fragility fractures associated with osteoporosis and osteopenia are a common cause of morbidity and mortality. Current methods of diagnosing low bone mineral density require specialized dual x-ray absorptiometry (DXA) scans. Plain hand radio...
Sex prediction through machine learning utilizing mandibular condyles, coronoid processes, and sigmoid notches features.
PloS one
Nov 15, 2024
Characteristics of the mandible structures have been relevant in anthropological and forensic studies for sex prediction. This study aims to evaluate the coronoid process, condyle, and sigmoid notch patterns in sex prediction through supervised machi...
Development and validation of a machine learning model to predict the risk of readmission within one year in HFpEF patients: Short title: Prediction of HFpEF readmission.
International journal of medical informatics
Nov 14, 2024
BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) is associated with elevated rates of readmission and mortality. Accurate prediction of readmission risk is essential for optimizing healthcare resources and enhancing patient outcomes...
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