Predictive value of a constructed artificial neural network model for microvascular invasion in hepatocellular carcinoma: A retrospective study

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Jan 15, 2025 (publication date) through Feb 9, 2025

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World Journal of Gastrointestinal Oncology

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1948-5204

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Retrospective Study

World J Gastrointest Oncol. Jan 15, 2025; 17(1): 96439
Published online Jan 15, 2025. doi: 10.4251/wjgo.v17.i1.96439

Table 1 Binary logistic regression analysis for microvascular invasion prediction

Variables	β	SE	Wald	df	P value	OR (95%CI)
Tumor maximum diameter	-0.074	0.588	0.016	1	0.900	0.929 (0.293-2.942)
Pseudocapsule	2.093	0.639	10.733	1	0.001	8.111 (2.318-28.373)
Tumor blood vessels	2.051	0.788	6.775	1	0.009	7.775 (1.660-36.421)
Cystic degeneration or necrosis	0.098	0.677	0.021	1	0.885	1.103 (0.293-4.4155)

OR: Odds ratio; CI: Confidence interval.

Citation: Nong HY, Cen YY, Lu SJ, Huang RS, Chen Q, Huang LF, Huang JN, Wei X, Liu MR, Li L, Ding K. Predictive value of a constructed artificial neural network model for microvascular invasion in hepatocellular carcinoma: A retrospective study. World J Gastrointest Oncol 2025; 17(1): 96439
URL: https://www.wjgnet.com/1948-5204/full/v17/i1/96439.htm
DOI: https://dx.doi.org/10.4251/wjgo.v17.i1.96439