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Risk Factors

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Development and validation of a prediction model for ED using machine learning: according to NHANES 2001-2004.

Scientific reports
Erectile Dysfunction (ED) is a form of sexual dysfunction in males that imposes significant health and financial burdens globally. Despite its high prevalence, diagnosing ED remains challenging due to the limitations of current diagnostic methods and...

Machine learning for outcome prediction in patients with non-valvular atrial fibrillation from the GLORIA-AF registry.

Scientific reports
Clinical risk scores that predict outcomes in patients with atrial fibrillation (AF) have modest predictive value. Machine learning (ML) may achieve greater results when predicting adverse outcomes in patients with recently diagnosed AF. Several ML m...

Artificial intelligence-based prediction of neurocardiovascular risk score from retinal swept-source optical coherence tomography-angiography.

Scientific reports
The recent rise of artificial intelligence represents a revolutionary way of improving current medical practices, including cardiovascular (CV) assessment scores. Retinal vascular alterations may reflect systemic processes such as the presence of CV ...

Predictive modeling of COVID-19 mortality risk in chronic kidney disease patients using multiple machine learning algorithms.

Scientific reports
The coronavirus disease 2019 (COVID-19) has a significant impact on the global population, particularly on individuals with chronic kidney disease (CKD). COVID-19 patients with CKD will face a considerably higher risk of mortality than the general po...

Machine learning model for age-related macular degeneration based on heavy metals: The National Health and Nutrition Examination Survey 2005 to 2008.

Scientific reports
Age-related macular degeneration (AMD) is the leading cause of blindness in older people in developed countries. It has been suggested that heavy metal exposure may be associated with the development of AMD, but most studies have focused on the effec...

Screening the Best Risk Model and Susceptibility SNPs for Chronic Obstructive Pulmonary Disease (COPD) Based on Machine Learning Algorithms.

International journal of chronic obstructive pulmonary disease
BACKGROUND AND PURPOSE: Chronic obstructive pulmonary disease (COPD) is a common and progressive disease that is influenced by both genetic and environmental factors, and genetic factors are important determinants of COPD. This study focuses on scree...

Prediction of recurrence-free survival and risk factors of sinonasal inverted papilloma after surgery by machine learning models.

European journal of medical research
OBJECTIVES: Our research aims to construct machine learning prediction models to identify patients proned to recurrence after inverted papilloma (IP) surgery and guide their follow-up treatment.

Predicting the risk of pulmonary infection after kidney transplantation using machine learning methods: a retrospective cohort study.

International urology and nephrology
PURPOSE: Pulmonary infection is the most common and serious complication after kidney transplantation that affects the survival of the transplanted kidney and the quality of life of patients. This study aims to construct a machine learning model for ...

Using interpretable machine learning methods to identify the relative importance of lifestyle factors for overweight and obesity in adults: pooled evidence from CHNS and NHANES.

BMC public health
BACKGROUND: Overweight and obesity pose a huge burden on individuals and society. While the relationship between lifestyle factors and overweight and obesity is well-established, the relative contribution of specific lifestyle factors remains unclear...

An enhanced machine learning algorithm for type 2 diabetes prognosis with a detailed examination of Key correlates.

Scientific reports
This study aimed to construct a high-performance prediction and diagnosis model for type 2 diabetic retinopathy (DR) and identify key correlates of DR. This study utilized a cross-sectional dataset of 3,000 patients from the People's Liberation Army ...