Endoscopic ultrasound artificial intelligence-assisted for prediction of gastrointestinal stromal tumors diagnosis: A systematic review and meta-analysis

doi:10.4253/wjge.v15.i8.528

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World Journal of Gastrointestinal Endoscopy

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1948-5190

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World J Gastrointest Endosc. Aug 16, 2023; 15(8): 528-539
Published online Aug 16, 2023. doi: 10.4253/wjge.v15.i8.528

Table 2 Artificial intelligence and experienced endoscopists’ diagnostic performance for gastrointestinal stromal tumor and differentiation of leiomyoma

	Prevalence (mean)	Sensitivity	Specificity	LR+	LR-	AUC	PTP+	PTP-
AI
GIST	68%	92%	80%	4.26	0.09	0.949	90%	16%
GIST vs GIL	70%¹	93%	90%	6.48	0.06	0.966	94%	12%
Endoscopists
GIST	67%	72%	70%	2.51	0.42	0.777	84%	46%
GIST vs GIL	67%¹	73%	75%	2.61	0.37	0.819	84%	43%

¹Gastrointestinal stromal tumor prevalence.

GIST: Gastrointestinal stromal tumor; GIL: Gastrointestinal leiomyoma; LR+: Likelihood ratio positive; LR-: Likelihood ratio negative; PTP+: Post-test probability positive; PTP-: Post-test probability negative; AUC: Area under the curve; AI: Artificial intelligence.

Citation: Gomes RSA, de Oliveira GHP, de Moura DTH, Kotinda APST, Matsubayashi CO, Hirsch BS, Veras MO, Ribeiro Jordão Sasso JG, Trasolini RP, Bernardo WM, de Moura EGH. Endoscopic ultrasound artificial intelligence-assisted for prediction of gastrointestinal stromal tumors diagnosis: A systematic review and meta-analysis. World J Gastrointest Endosc 2023; 15(8): 528-539
URL: https://www.wjgnet.com/1948-5190/full/v15/i8/528.htm
DOI: https://dx.doi.org/10.4253/wjge.v15.i8.528