Artificial Intelligence Used to Predict Postoperative Nausea

Serdar HocamAuthor & Editor

The role of artificial intelligence models in predicting common complications in surgical patients receiving general anesthesia is being examined.

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A systematic review study has been published examining artificial intelligence and machine learning models to predict postoperative nausea and vomiting conditions occurring after general anesthesia.

Anesthesia in Surgical Procedures

General anesthesia enables millions of surgical operations to be performed every year. However, this perioperative period remains susceptible to adverse physiological and clinical events that vary in timing, severity, and mechanism.

The Problem of Nausea and Vomiting

Postoperative nausea and vomiting rank among the most common complications following general anesthesia. This condition can affect approximately 30 percent of all surgical patients and can negatively impact the recovery process, patient satisfaction, clinical outcomes, and hospital finances.

Artificial Intelligence-Based Models

Risk prediction in anesthesia has traditionally relied on clinical evaluations and limited scoring systems. Artificial intelligence-based models, on the other hand, are capable of integrating numerous heterogeneous and time-varying variables.

Scope of the Review Study

This systematic review evaluated artificial intelligence models predicting postoperative nausea and vomiting as a primary outcome in patients undergoing surgery under general anesthesia. The research was conducted in accordance with the PRISMA 2020 statement and PROSPERO protocol registration.