Abstract Background Intensive Care Unit (ICU) readmissions represent both a health risk for
patients, with increased mortality rates and overall health deterioration, and a financial …

Unplanned intensive care unit (ICU) readmission rate is an important metric for evaluating
the quality of hospital care. Efficient and accurate prediction of ICU readmission risk can not …

Healthcare knowledge graphs (HKGs) have emerged as a promising tool for organizing
medical knowledge in a structured and interpretable way, which provides a comprehensive …

Sepsis is the third-highest mortality disease in intensive care units (ICUs). In this paper, we
proposed a deep learning model for predicting the severity of sepsis patients. Most existing …

ICU readmissions are costly and most of the early ICU readmissions in the United States are
potentially avoidable. After the US Govts push towards reducing avoidable readmissions …

Unplanned intensive care units (ICU) readmissions and in-hospital mortality of patients are
two important metrics for evaluating the quality of hospital care. Identifying patients with …

Knowledge graphs (KGs) are a popular way to organise information based on ontologies or
schemas. Despite advances in KGs, representing knowledge remains a non-trivial task …

Clinical predictive models often rely on patients' electronic health records (EHR), but
integrating medical knowledge to enhance predictions and decision-making is challenging …

The ability to perform accurate prognosis is crucial for proactive clinical decision making,
informed resource management and personalised care. Existing outcome prediction models …

Disease prediction based on patients' historical admission records is an essential task in the
medical field, but current predictive models often lack interpretability, which is a critical …