AIMC Topic: Surgical Procedures, Operative

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Machine learning-based cardiovascular risk calculator for non-cardiac surgery.

Open heart
BACKGROUND: Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least one cardiovascular risk factor. It is estimated that the 30-day mortality is between 0.5% and 2%.The main objective of this st...

Improved American College of Surgeons NSQIP Hospital Benchmarking with Risk Adjustment for Many CPT Codes Rather Than Just the Principal Code.

Journal of the American College of Surgeons
BACKGROUND: Because of technical limitations inherent to logistic regression, NSQIP benchmarking has historically risk adjusted for procedure using only 1 principal CPT code among other predictors. This has the potential to create bias (favorable or ...

A roadmap of artificial intelligence applications in pediatric surgery: a comprehensive review of applications, challenges, and ethical considerations.

Pediatric surgery international
Artificial intelligence (AI) and machine learning (ML) are rapidly transforming healthcare, with growing interest in their application to rare pediatric surgical conditions. In these settings, limited data availability often brakes traditional resear...

Intraoperative hypotension prediction in cardiac and noncardiac procedures: is HPI truly worthwhile? A systematic review and meta-analysis.

BMC anesthesiology
BACKGROUND: Intraoperative hypotension (IOH), defined as a mean arterial pressure (MAP) below 65 mmHg, is a common complication during surgery and is associated with significant postoperative morbidity, including acute kidney injury, myocardial injur...

Identifying patterns of high intraoperative blood pressure variability in noncardiac surgery using explainable machine learning: a retrospective cohort study.

Annals of medicine
BACKGROUND: High intraoperative blood pressure variability (HIBPV) is significantly associated with postoperative adverse complications. However, practical tools to characterize perioperative factors associated with HIBPV remain limited. This study a...

The Role of Artificial Intelligence in Surgery: Predictive Analytics, Intraoperative Assistance, and Education.

Anesthesiology clinics
Artificial intelligence (Al) is transforming surgical care by enhancing risk prediction, preoperative planning, and surgical education. Unlike traditional statistical tools, Al-especially machine learning-can process complex, nonlinear clinical data ...

Using the Geriatric Emergency Perioperative Risk Index Derived From Artificial Intelligence Algorithms to Predict Outcomes of Geriatric Emergency General Surgery.

The Journal of surgical research
INTRODUCTION: The objective of this study was to employ artificial intelligence (AI) technology for the development of a model that can accurately forecast the outcome of emergency general surgery (EGS) in elderly patients. Additionally, an innovativ...

Developing a Machine Learning Model for Predicting 30-Day Major Adverse Cardiac and Cerebrovascular Events in Patients Undergoing Noncardiac Surgery: Retrospective Study.

Journal of medical Internet research
BACKGROUND: Considering that most patients with low or no significant risk factors can safely undergo noncardiac surgery without additional cardiac evaluation, and given the excessive evaluations often performed in patients undergoing intermediate or...

Impact of AI on Access to Care a Three-Pronged Approach for Enhancing Access to Surgical Care: Lessons From Electrical Safety and the Impact of AI on Health Equity.

The American surgeon
As we enter the 21st century, a new wave of transformation is occurring in health care, mainly through artificial intelligence (AI). Like electricity, AI is a powerful tool that can either harm or heal, depending on how it is managed. In 2015, the Un...

Perioperative risk assessment for emergency general surgery in those with multimorbidity or frailty.

Current opinion in critical care
PURPOSE OF REVIEW: This review explores advances in risk stratification tools and their applicability in identifying and managing high-risk emergency general surgery (EGS) patients.