Artificial intelligence in anesthesia and perioperative medicine
Abstract The rapid development of artificial intelligence (AI) technology, in particular AlphaFold, has greatly improved protein structure prediction and design, reshaped protein biology and expanded research directions in anesthesiology and perioperative medicine. AI relies on deep learning to accurately model key proteins, such as G protein-coupled receptors, to aid drug development. In perioperative medicine, AI improves individualized treatment, patient safety and postoperative recovery through biomarker identification and anesthetic protocol optimization. In addition, AI accelerates anesthetic drug discovery, optimizes drug screening, toxicity prediction and clinical trials to improve the efficiency of research and development. Whilst data interpretation and diversity remain challenges, the continued advancement of AI in the fields of precision medicine and perioperative management will promote the development of individualized anesthesia and precision medicine.
Authors
- Chao Liu (ORCID: https://orcid.org/0000-0001-6473-2292)
- Jianzhong Zheng (ORCID: https://orcid.org/0000-0002-0430-6723)
- Qiang Fu (ORCID: https://orcid.org/0000-0002-3232-4224)
- Yufeng Zhang (ORCID: https://orcid.org/0000-0001-7956-7250)
- Fei Qin (ORCID: https://orcid.org/0000-0002-5732-7827)
Institutions
- Third People's Hospital of Chengdu (CN)
- Thang Long University (VN)
- Panzhihua Central Hospital (CN)
Publication Details
- Journal
- Anesthesiology and Perioperative Science
- Published
- 2025-05-28
- DOI
- https://doi.org/10.1007/s44254-025-00107-4
- Citations
- 4
- Primary Topic
- Cardiac, Anesthesia and Surgical Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 5.55