Artificial intelligence revolutionizing anesthesia management: advances and prospects in intelligent anesthesia...

Area of Science:

• Medical Informatics
• Anesthesiology
• Artificial Intelligence

Background:

• Artificial intelligence (AI) is increasingly integrated into medical applications.
• Anesthesia, crucial for surgery and pain management, faces data collection hurdles for AI integration.
• Existing AI applications in medicine often leverage easily processed signals like ECG or EEG, unlike anesthesia data.

Purpose of the Study:

• To provide a comprehensive review of AI-based methods in anesthesia.
• To explore AI applications across the preoperative, intraoperative, and postoperative phases of anesthesia.
• To offer guidance for anesthesiologists on utilizing advanced AI techniques.

Main Methods:

• Review of existing literature on AI in anesthesia.
• Overview of fundamental AI concepts.
• Discussion of AI applications categorized by anesthesia phases (preoperative, intraoperative, postoperative).

Main Results:

• AI applications are emerging in all phases of anesthesia, despite data acquisition challenges.
• The review categorizes and discusses current AI uses in preoperative, intraoperative, and postoperative anesthesia.
• Future development trends in intelligent anesthesia are identified.

Conclusions:

• The integration of AI in anesthesia is poised for significant growth.
• Addressing data collection challenges is key to unlocking AI's full potential in anesthesia.
• This review aims to guide anesthesiologists in leveraging AI for improved patient diagnosis and treatment.