Artificial intelligence-based lung nodule detection for pulmonary arteriovenous fistulas on chest computed tomography

doi:10.4329/wjr.v18.i4.119851

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World Journal of Radiology

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1949-8470

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

Retrospective Cohort Study

Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.

World J Radiol. Apr 28, 2026; 18(4): 119851
Published online Apr 28, 2026. doi: 10.4329/wjr.v18.i4.119851

Table 1 Baseline characteristics of the study population

Characteristic		Value
Age (years)		59 (16-85)
Sex	Male	6
Sex	Female	15
Underlying disease	Hereditary hemorrhagic telangiectasia	2
Symptoms	Dyspnea	4
	Hemoptysis	1
	Asymptomatic	16
Comorbidities	Heart failure	2
Comorbidities	Cerebral infarction	3
SpO₂ (%)		96 (94-99)
Treatment	Endovascular embolization	14
	Surgery	2
	Conservative management	5

Data are presented as median (range) or number of patients.

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Citation: Azama K, Tsuchiya N, Toyosato S, Yonemoto K, Nishie A. Artificial intelligence-based lung nodule detection for pulmonary arteriovenous fistulas on chest computed tomography. World J Radiol 2026; 18(4): 119851
URL: https://www.wjgnet.com/1949-8470/full/v18/i4/119851.htm
DOI: https://dx.doi.org/10.4329/wjr.v18.i4.119851

Azama K, Tsuchiya N, Toyosato S, Yonemoto K, Nishie A. Artificial intelligence-based lung nodule detection for pulmonary arteriovenous fistulas on chest computed tomography. World J Radiol 2026; 18(4): 119851 [PMID: 42057839 DOI: 10.4329/wjr.v18.i4.119851]

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