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World J Methodol. Sep 20, 2026; 16(3): 117916
Published online Sep 20, 2026. doi: 10.5662/wjm.117916
Published online Sep 20, 2026. doi: 10.5662/wjm.117916
Artificial intelligence in onco-anaesthesia: Current applications, challenges, and future directions
Prashant Sirohiya, Prateek Maurya, Saurabh Vig, Balbir Kumar, Raghav Gupta, Shweta Bhopale, Anuja Pandit, Department of Onco-Anaesthesia and Palliative Medicine, National Cancer Institute (Jhajjar), AIIMS, New Delhi 110029, Delhi, India
Nishkarsh Gupta, Brajesh Kumar Ratre, Department of Onco-Anaesthesia and Palliative Medicine, Dr. B.R.A. Institute Rotary Cancer Hospital, AIIMS, New Delhi 110029, Delhi, India
Sidharth Puri, Department of Critical Care Medicine, SGHS Hospital, Mohali 140308, Punjab, India
Co-corresponding authors: Prashant Sirohiya and Prateek Maurya.
Author contributions: Sirohiya P and Pandit A designed the research study; Maurya P, Gupta N, Ratre BK, Vig S, Puri S, and Kumar B performed the literature search and analyzed the data; Gupta R and Bhopale S contributed analytical tools; Sirohiya P and Maurya P wrote the manuscript. All authors have read and approved the final manuscript. Sirohiya P conceptualized the topic, structured the manuscript, and supervised the overall academic direction of the work. Maurya P played a major role in conducting the literature review, critically appraising the evidence, drafting substantial portions of the manuscript, and revising the content for intellectual depth and clarity. Both authors collaboratively shaped the final manuscript, refined key arguments, ensured scientific rigor, and take joint responsibility for the integrity of the work. Given their shared leadership in manuscript development and their commitment to managing editorial communication and post-publication correspondence, designation as co-corresponding authors appropriately reflects their equal intellectual contribution and shared accountability.
AI contribution statement: AI tools such as ChatGPT and Grammarly are used for language optimization and improvement of expression clarity. Any part of this manuscript (including the abstract, introduction, materials and methods, results, discussion, or conclusion) is not entirely generated by AI. All content is based on the original work, analysis and interpretation of the author. AI tools are only used for minor polishing of language and providing writing assistance to enhance readability. They are not used for data analysis or generating scientific content. AI tools did not participate in the research design, data interpretation or the derivation of scientific conclusions. The images included in this manuscript were not generated by AI.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
Corresponding author: Prashant Sirohiya, Assistant Professor, Department of Onco-Anaesthesia and Palliative Medicine, National Cancer Institute (Jhajjar), AIIMS, Badsa, New Delhi 110029, Delhi, India. prashantsirohiya@aiims.edu
Received: December 18, 2025
Revised: January 21, 2026
Accepted: February 24, 2026
Published online: September 20, 2026
Processing time: 203 Days and 23.9 Hours
Revised: January 21, 2026
Accepted: February 24, 2026
Published online: September 20, 2026
Processing time: 203 Days and 23.9 Hours
Core Tip
Core Tip: Artificial intelligence (AI) is redefining onco-anaesthesia by enabling the construction of “digital twins” for cancer patients, allowing clinicians to simulate and optimize anesthetic care before the first incision. This review highlights how AI algorithms, ranging from computer vision to natural language processing, are being deployed to predict adverse events like hypotension and delirium with unprecedented accuracy. By modulating the neuroendocrine stress response and facilitating opioid-sparing strategies, AI-augmented anesthesia may improve long-term cancer survival. However, the successful integration of these tools requires rigorous validation, ethical oversight, and a commitment to explainable AI to ensure clinical trust and patient safety.