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

Background Scalable and accurate health outcome prediction using electronic health record
(EHR) data has gained much attention in research recently. Previous machine learning …

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 …

Existing machine learning methods typically assume consistency in how semantically
equivalent information is encoded. However, the way information is recorded in databases …

Clinical decision-making in healthcare is already being influenced by predictions or
recommendations made by data-driven machines. Numerous machine learning applications …

Accurate knowledge of a patient's disease state and trajectory is critical in a clinical setting.
Modern electronic healthcare records contain an increasingly large amount of data, and the …

Objectives To develop and evaluate a high-dimensional, data-driven model to identify
patients at high risk of clinical deterioration from routinely collected electronic health record …

The all-condition prediction of patient mortality at the time of hospital admission has
significant clinical value and broader implications for patient care and clinical decision …

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 …

The meaningful use of electronic medical records (EMR) will come from effective clinical
decision support (CDS) applied to physician orders, the concrete manifestation of clinical …