Artificial intelligence in onco-anaesthesia: Current applications, challenges, and future directions

Table 2 Artificial intelligence-driven predictive models for oncological outcomes

Outcome domain	Specific target	AI methodology	Key findings/performance	Clinical implication
Hemodynamics	Intraoperative hypotension	Gradient boosting; CNN-RNN	AUROC 0.94; Accuracy 0.88; 6 endotypes[21,22]	Preemptive endotype-specific treatment
Hemodynamics	Anastomotic leakage (esophagectomy)	Threshold analysis	MAP < 65 mmHg: OR 1.02 per 10-minute[20]	Avoid prolonged hypotension
Complications	Anastomotic leakage (colorectal)	ANN	Superior sensitivity vs surgeons[13]	Early intervention/diversion
Complications	CD ≥ 3 complications	XGBoost with SHAP	AUROC 0.77 (train), 0.73 (test)[6]	Transparent risk stratification
Neurological	Postoperative delirium	XGBoost (AI-delirium guard)	AUC 0.85[31]	Targeted prevention; web tool1
Pain	Chronic postsurgical pain	Stacking ensemble (EHR + Wearable)	AUC 0.90; 89% accuracy[35]	Precision analgesia intervention
Prognosis	Recurrence (NSCLC)	Cox regression	Stage I: P = 0.036; stage II-III: NS[25]	Stage-specific counseling
Prognosis	Metastasis (cT1 lung)	Random forest (MoLPre)	AUC 0.92 (internal validation), 0.90 (external validation)[17]	Online prediction tool2
Prognosis	Early recurrence (NSCLC)	Stacking ensemble	AUC 0.81 (test), 0.80 (external validation)[16]	Adjuvant therapy decisions
Liver surgery	Post-Hepatectomy failure	Multimodal ML (radiomics + clinical)	Outperformed MELD/Child-Pugh[14]	Resection vs transplant selection

¹https://ai-delirium-guard.streamlit.app.

²https://molpre.cqmu.edu.cn/.

AI: Artificial intelligence; CNN: Convolutional neural network; RNN: Recurrent neural network; AUROC: Area under receiver operating characteristic curve; MAP: Mean arterial pressure; OR: Odds ratio; ANN: Artificial neural network; CD: Clavien-Dindo; SHAP: SHapley Additive exPlanations; AUC: Area under curve; NSCLC: Non-small cell lung cancer; NS: Not significant; ML: Machine learning; MELD: Model for end-stage liver disease.