Background The number of studies applying machine learning (ML) to predict acute kidney
injury (AKI) has grown steadily over the past decade. We assess and critically appraise the …

Background and aims Understanding the age-related trend of risk in high blood pressure
(BP) is important for preventing heart failure and cardiovascular diseases. But such a trend …

Background Surgical patients are complex, vulnerable, and prone to postoperative
complications that can potentially be mitigated with quality perioperative risk assessment …

Background Anaesthesiologists might be able to mitigate risk if they know which patients are
at greatest risk for postoperative complications. This trial examined the impact of machine …

BACKGROUND: Machine learning models can help anesthesiology clinicians assess
patients and make clinical and operational decisions, but well-designed human-computer …

Background Post-operative complications present a challenge to the healthcare system due
to the high unpredictability of their incidence. Socioeconomic conditions have been …

Background Handoffs or care transitions from the operating room (OR) to intensive care unit
(ICU) are fragmented and vulnerable to communication errors. Although protocols and …

Introduction: Perioperative morbidity is a public health priority, and surgical volume is
increasing rapidly. With advances in technology, there is an opportunity to research the …

Background: More than four million people die each year in the month following surgery,
and many more experience complications such as acute kidney injury. Some of these …

Background: Anaesthesiology clinicians can implement risk mitigation strategies if they
know which patients are at greatest risk for postoperative complications. Although machine …