BACKGROUND: Acute myocardial infarction (AMI) remains a leading cause of hospitalization and death in China. Accurate mortality prediction of inpatient is crucial for clinical decision-making of non-ST-segment elevation myocardial infarction (NSTEMI)...
Journal of cardiothoracic and vascular anesthesia
39779429
BACKGROUND: The incidence, mortality, and readmission rates for acute heart failure (AHF) are high, and the in-hospital mortality for AHF patients in the intensive care unit (ICU) is higher. However, there is currently no method to accurately predict...
Computer methods and programs in biomedicine
39709743
BACKGROUND: The fusion of multi-modal data has been shown to significantly enhance the performance of deep learning models, particularly on medical data. However, missing modalities are common in medical data due to patient specificity, which poses a...
The international journal of cardiovascular imaging
39786626
Amid an aging global population, heart failure has become a leading cause of hospitalization among older people. Its high prevalence and mortality rates underscore the importance of accurate mortality prediction for swift disease progression assessme...
BACKGROUND: Prognosis prediction in the intensive care unit (ICU) traditionally relied on physiological scoring systems based on clinical indicators at admission. Electrocardiogram (ECG) provides easily accessible information, with heart rate variabi...
Artificial intelligence (AI) is being increasingly applied in healthcare to improve patient care and clinical outcomes. We previously developed an AI model using ICD-10 (International Classification of Diseases, Tenth Revision) codes with other clini...
BACKGROUND: Ventilator-associated pneumonia (VAP) is a common nosocomial infection in ICU, significantly associated with poor outcomes. However, there is currently a lack of reliable and interpretable tools for assessing the risk of in-hospital morta...
Community-acquired pneumonia (CAP) is associated with high mortality rates and often results in prolonged hospital stays. The potential of machine learning to enhance prediction accuracy in this context is significant, yet clinicians often lack the p...
BACKGROUND: The efficiency of machine learning (ML) based predictive models in predicting in-hospital mortality for heart failure (HF) patients is a topic of debate. In this context, this study's objective is to conduct a meta-analysis to compare and...
Journal of the American Medical Informatics Association : JAMIA
39873685
OBJECTIVE: Prediction of mortality in intensive care unit (ICU) patients typically relies on black box models (that are unacceptable for use in hospitals) or hand-tuned interpretable models (that might lead to the loss in performance). We aim to brid...