[Artificial Intelligence in Anesthesiology - Focus on Hemodynamics]

Area of Science:

• Anesthesiology and Intensive Care Medicine
• Medical Artificial Intelligence

Background:

• Artificial intelligence (AI) is increasingly integrated into anesthesiology and intensive care.
• Hemodynamic assessment, specifically predicting hypotension via arterial blood pressure waveform analysis, is a key AI application.
• While AI can reduce hypotension severity and duration, evidence for reduced morbidity and mortality is pending.

Purpose of the Study:

• To review the current and potential applications of AI in anesthesiology and intensive care medicine.
• To identify limitations and challenges to AI implementation in these fields.

Main Methods:

• Review of current AI applications in hemodynamic monitoring.
• Discussion of potential future AI uses in anesthesiology and intensive care.
• Analysis of implementation barriers, including technological and human factors.

Main Results:

• AI effectively predicts hypotension, reducing episode severity and duration.
• Numerous potential AI applications exist, but most are in early development.
• Key limitations include the human factor (clinician monitoring and workflow adaptation) and unresolved legal liability issues.

Conclusions:

• AI shows promise in hemodynamic assessment but requires further validation regarding patient outcomes.
• Successful AI implementation hinges on addressing the human factor and establishing clear legal frameworks for AI-assisted decision-making.
• Future research should focus on robust clinical trials and legal/regulatory clarity.