Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is a leading cause of hospitalization and death in COPD patients. Machine learning (ML) approach is powerful but has a "black box" issue with an undirect interpretation of the ML te...
This study presents a machine learning-driven model predicting all-cause mortality two years in advance using administrative health data focused on diabetic patients. Integrating hospitalization records, emergency department data, demographics, and c...
This study aims to enhance individual hypertension risk prediction in Indonesia using machine learning (ML) models. The research investigates the predictive accuracy of models with and without incorporating personal hypertension history, seeking to u...
BACKGROUND: Depressive symptoms and multiple chronic diseases (MCDs) significantly contribute to the global disease burden among middle-aged and older adults, while few studies have considered the long-term dynamics of depressive symptoms or employed...
Talk and Deteriorate refers to a clinical course where a patient is able to speak immediately after a traumatic brain injury but subsequently deteriorates in consciousness. Talk and Deteriorate outcomes are poor, and reliable prediction may help impr...
BACKGROUND: Cardiovascular disease remains the predominant cause of morbidity and mortality in individuals with type 2 diabetes mellitus (T2DM). Traditional risk models are limited in predictive accuracy. Pericoronary adipose tissue (PCAT), a novel i...
OBJECTIVE: The relationship between depression and obstructive sleep apnea (OSA) remains controversial. Therefore, this study aims to explore their association and utilize machine learning models to predict OSA among individuals with depression withi...
OBJECTIVE: Primary palmar hyperhidrosis (PPH), characterised by excessive palm sweating, significantly impacts patients' physiology, psychology, self-esteem, work, life and social interactions. The incidence of depression is higher among PPH patients...
BACKGROUND: The growing prevalence of obesity in adolescents around the world poses a major threat to public health. This research uses machine learning models to examine the main causes of obesity, in contrast to standard information that typically ...
BACKGROUND: Previous studies have demonstrated that the triglyceride-glucose (TyG) index in combination with the estimated glucose disposal rate (eGDR) could predict mortality risks in the normal population. Our studies have focused on their additive...
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