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Risk Factors

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Predicting early mortality in hemodialysis patients: a deep learning approach using a nationwide prospective cohort in South Korea.

Scientific reports
Early mortality after hemodialysis (HD) initiation significantly impacts the longevity of HD patients. This study aimed to quantify the effect sizes of risk factors on mortality using various machine learning approaches. A cohort of 3284 HD patients ...

Oral Microbe Community and Pyramid Scene Parsing Network-based Periodontitis Risk Prediction.

International dental journal
BACKGROUND: Periodontitis (PD) is a common chronic inflammatory disease affecting the gums and supporting tooth structures. It is often diagnosed only after significant irreversible tissue damage - such as gum recession and bone loss - has occurred, ...

Using supervised machine learning algorithms to predict bovine leukemia virus seropositivity in dairy cattle in Florida: A 10-year retrospective study.

Preventive veterinary medicine
Supervised machine-learning (SML) algorithms are potentially powerful tools that may be used for screening cows for infectious diseases such as bovine leukemia virus (BLV) infection. Here, we compared six different SML algorithms to identify the most...

Development, validation and economic evaluation of a machine learning algorithm for predicting the probability of kidney damage in patients with hyperuricaemia: protocol for a retrospective study.

BMJ open
INTRODUCTION: Accurate identification of the risk factors is essential for the effective prevention of hyperuricaemia (HUA)-related kidney damage. Previous studies have established the efficacy of machine learning (ML) methodologies in predicting kid...

Developing predictive models for residual back pain after percutaneous vertebral augmentation treatment for osteoporotic thoracolumbar compression fractures based on machine learning technique.

Journal of orthopaedic surgery and research
BACKGROUND: Machine learning (ML) has been widely applied to predict the outcomes of numerous diseases. The current study aimed to develop a prognostic prediction model using machine learning algorithms and identify risk factors associated with resid...

Analysis of the Predictors of Mortality from Ischemic Heart Diseases in the Southern Region of Brazil: A Geographic Machine-Learning-Based Study.

Global heart
BACKGROUND: Mortality due to ischemic heart disease (IHD) is heterogeneously distributed globally, and identifying the sites most affected by it is essential in developing strategies to mitigate the impact of the disease, despite the complexity resul...

A Predictive Model Integrating AI Recognition Technology and Biomarkers for Lung Nodule Assessment.

The Thoracic and cardiovascular surgeon
BACKGROUND:  Lung cancer is the most prevalent and lethal cancer globally, necessitating accurate differentiation between benign and malignant pulmonary nodules to guide treatment decisions. This study aims to develop a predictive model that integrat...

Identification and optimization of relevant factors for chronic kidney disease in abdominal obesity patients by machine learning methods: insights from NHANES 2005-2018.

Lipids in health and disease
BACKGROUND: The intake of dietary antioxidants and glycolipid metabolism are closely related to chronic kidney disease (CKD), particularly among individuals with abdominal obesity. Nevertheless, the cumulative effect of multiple comorbid risk factors...

Predictive analysis of bullying victimization trajectory in a Chinese early adolescent cohort based on machine learning.

Journal of affective disorders
BACKGROUND: The development of bullying victimization among adolescents displays significant individual variability, with general, group-based interventions often proving insufficient for partial victims. This study aimed to conduct a machine learnin...