Table 4.

Effects of artificial intelligence for the application of allergic rhinitis and urticaria.

Year	Author	Specific Artificial Intelligence	Reference	Diagnose/prediction/treatment/management	efficiency
2015	Christopher, et al	CBA; SVM	70	Diagnosis	CBA: SE (94.0%); SP (94.2%); precision (92.3%); AC (94.17%) SVM: SE (93.4%); SP (93.1%); precision (90.8%); AC (93.24%)
2021	Huang, et al	Random forest model	67	Prediction	AUROC: AR (84%); AD (83%)
2022	Betul, et al	CNN	71	Diagnosis	AC: 98.3%; precision: 99%; Recall: 98%
2022	Malizia, et al	Latent class analysis (LCA)	73	Diagnosis	Two subtypes of AR have been identified.
2022	Türk, et al	Cluster analysis	82	Diagnosis	Four groups were identified.
2023	Lisha, et al	smart watch	75	Management	Patients in the intervention group showed improved medication adherence and significantly reduced nasal symptoms.
2024	Fan, et al	ChatGPT	107	Management	Correctly answered 80% of the questions
2024	Simon, et al	ChatGPT	108	Management	Likert scale score: Differences in accuracy scores.
2024	Hyeon, et al	Multi-variable spatiotemporal graph convolutional network (MST-GCN)	68	Prediction	AC: AR (88%); AD (68%); Asthma (86%) R2: AR (96%); AD (75%); Asthma (93%)
2024	Dai, et al	Ensemble learning algorithms	69	Diagnosis	ARF-OOBEE: AUROC (98.30%); SE (89.49%); SP (98.05%); AC (97.04%) GC Forest: AUROC (95.28%); SE (89.80%); SP (98.10%); AC (97.48%)
2024	Junhyoung, et al	Artificial intelligence (AI)-based new drug development platform	74	Treatment	Successfully screened potential therapeutic drugs for AR.
2024	Hojae, et al	Random forest model	77	Management; Prediction	SE: 83.33%; SP: 82.58%; AC: 82.59%; AUROC: 89.87%
2024	Taig Mac Carthy, et al	CNN	79	Diagnosis	BAC: 0.72
2024	Lee1, et al	Deep learning	80	Diagnosis	Wheal: SE (56.21%); SP (99.95%); AC (99.85%) Erythema: SE (57.87%); SP (97.97%); AC (96.60%)