Artificial Intelligence in Anesthesiology and Perioperative Medicine: From Clinical Decision Support to Autonomous Systems
The Algorithmic Clinician: AI’s Revolution in Specialty Medicine, HALE KOKSOY,USAME OMER OSMANOGLU,HATICE SEYMA AKCA, Editör, Nobel Yayınevi, İstanbul, ss.457-466, 2026
- Yayın Türü: Kitapta Bölüm / Mesleki Kitap
- Basım Tarihi: 2026
- Doi Numarası: 10.69860/nobel.9786258984200
- Yayınevi: Nobel Yayınevi
- Basıldığı Şehir: İstanbul
- Sayfa Sayıları: ss.457-466
- Editörler: HALE KOKSOY,USAME OMER OSMANOGLU,HATICE SEYMA AKCA, Editör
- Erzincan Binali Yıldırım Üniversitesi Adresli: Evet
Özet
Artificial intelligence (AI) is rapidly transforming the field of anaesthesiology and perioperative medicine by enabling data-driven, predictive, and personalised clinical decision-making. This review provides a comprehensive overview of current and emerging applications of AI across the perioperative continuum, including preoperative assessment, intraoperative management, postoperative care and intensive care practice.
In the preoperative setting, AI-based models enhance risk stratification, predict postoperative complications, and improve difficult airway assessment through advanced data integration and image analysis. During the intraoperative period, AI facilitates real-time monitoring and prediction of hemodynamic instability, optimises anaesthetic drug dosing, and improves the accuracy of anaesthetic depth monitoring using advanced machine learning algorithms. Additionally, AI-supported systems contribute to quality control and workflow optimisation within perioperative environments.
In ultrasound-guided regional anaesthesia and point-of-care ultrasonography (POCUS), AI enhances anatomical recognition, improves procedural safety, and accelerates training processes through automated image interpretation and guidance systems. In the postoperative and intensive care settings, AI enables early detection of complications, supports ventilator weaning decisions, and contributes to personalised recovery pathways.
Despite these advancements, significant ethical and legal challenges remain, including issues related to transparency, algorithmic bias, data security, and medico-legal responsibility. The limitations of fully autonomous systems, exemplified by the SEDASYS system, highlight the continued necessity of clinician supervision.
AI is not expected to replace anaesthesiologists but rather to redefine their role toward supervising intelligent systems, interpreting complex data, and ensuring patient-centred care. The future of anaesthesiology will likely depend on a hybrid model integrating human expertise with AI-supported decision systems, with a strong emphasis on safety, ethics, and clinical accountability.
Keywords: Artificial Intelligence; Anaesthesiology; Perioperative Medicine; Clinical Decision Support Systems; Difficult Airway Prediction; Hemodynamic Monitoring; Anaesthetic Depth; Target Controlled Infusion; Ultrasound Guided Regional Anaesthesia; Point-of-Care Ultrasound; Intensive Care; ERAS; Machine Learning; PAtient Safety; Medical Ethics.