Most surgeons are skeptical as to the feasibility of autonomous actions in surgery.
Interestingly, many examples of autonomous actions already exist and have been around for …

Background Machine learning (ML) is increasingly used in research for subtype definition
and risk prediction, particularly in cardiovascular diseases. No existing ML models are …

Improving predictive models for intensive care unit (ICU) inpatients requires a new strategy
that periodically includes the latest clinical data and can be updated to reflect local …

This study evaluated prediction performance of three different machine learning (ML)
techniques in predicting opioid misuse among US adolescents. Data were drawn from the …

Background The utilization of artificial intelligence and machine learning as diagnostic and
predictive tools in perioperative medicine holds great promise. Indeed, many studies have …

In the field of anaesthesia, artificial intelligence (AI) has become a game-changing
technology. Applications of AI include keeping records, monitoring patients, calculating and …

Background Risk stratification plays a central role in anesthetic evaluation. The use of Big
Data and machine learning (ML) offers considerable advantages for collection and …

The depth and breadth of data produced in the modern cardiac intensive care unit (CICU)
poses challenges to clinicians and researchers. Artificial intelligence (AI) and machine …

Artificial intelligence (AI) is rapidly emerging in healthcare, yet applications in surgery
remain relatively nascent. Here we review the integration of AI in the field of surgery …

Purpose An indication for surgical therapy includes balancing benefits against risk, which
remains a key task in all surgical disciplines. Decisions are oftentimes based on clinical …