Pathological analysis of hesperetin-derived small cell lung cancer by artificial intelligence technology under fiberoptic bronchoscopy

Lung cancer is one of the most common tumors. There are 1.8 million new cases worldwide each year, accounting for about 13% of all new tumors. Lung cancer is the most important cause of cancer-related deaths. 1.4 million people die of lung cancer each year. This article uses artificial intelligence...

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Autores principales:	Xiaoli Zhang, Ziying Yu
Formato:	article
Lenguaje:	EN
Publicado:	AIMS Press 2021
Materias:	hesperetin derivatives lung small cell carcinoma circulating cell detection technology fiberoptic bronchoscopy Biotechnology TP248.13-248.65 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/ed8db61b85114d89af48218ec316d4ae
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spelling	oai:doaj.org-article:ed8db61b85114d89af48218ec316d4ae2021-11-29T01:16:06ZPathological analysis of hesperetin-derived small cell lung cancer by artificial intelligence technology under fiberoptic bronchoscopy10.3934/mbe.20214231551-0018https://doaj.org/article/ed8db61b85114d89af48218ec316d4ae2021-09-01T00:00:00Zhttps://www.aimspress.com/article/doi/10.3934/mbe.2021423?viewType=HTMLhttps://doaj.org/toc/1551-0018Lung cancer is one of the most common tumors. There are 1.8 million new cases worldwide each year, accounting for about 13% of all new tumors. Lung cancer is the most important cause of cancer-related deaths. 1.4 million people die of lung cancer each year. This article uses artificial intelligence technology to analyze the pathology of hesperetin-derived small cell lung cancer under fiberoptic bronchoscopy. This article takes 48 lung slice samples as the research object. Among them, 36 cases of lung small cell carcinoma have history slices from Lhasa City Institute of Biology, the patient has complete cases, and the other 12 normal lung slices come from Xinjiang Biotechnology Laboratory. In this paper, the above-mentioned 36 lung cancer slices became the study group, and 12 normal slices became the reference group. This article presents a method for hesperetin-fiber bronchoscope to study the pathological mechanism of lung small cell carcinoma (H-FBS), which is used to study slices. The above-mentioned 48 samples were taken for slice observation. First, the 48 slices were technically tested by artificial intelligence fiber bronchoscope combined with hesperetin derivatives, and then the slice observation results were verified by CTC technology. In addition, in each step, the C5orf34 in the tissue is detected separately, which is beneficial to adjust the content of C5orf34 so that the treatment of lung cancer can control the development of lung cancer under fiberoptic bronchoscopy. Experimental results show that the diagnostic accuracy rate of this method is 97.9%, which is higher than that of lung biopsy (89%); compared with multiple CTC detection, the cost is low and the time is shor.Xiaoli Zhang Ziying YuAIMS Pressarticlehesperetin derivativeslung small cell carcinomacirculating cell detection technologyfiberoptic bronchoscopyBiotechnologyTP248.13-248.65MathematicsQA1-939ENMathematical Biosciences and Engineering, Vol 18, Iss 6, Pp 8538-8558 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	hesperetin derivatives lung small cell carcinoma circulating cell detection technology fiberoptic bronchoscopy Biotechnology TP248.13-248.65 Mathematics QA1-939
spellingShingle	hesperetin derivatives lung small cell carcinoma circulating cell detection technology fiberoptic bronchoscopy Biotechnology TP248.13-248.65 Mathematics QA1-939 Xiaoli Zhang Ziying Yu Pathological analysis of hesperetin-derived small cell lung cancer by artificial intelligence technology under fiberoptic bronchoscopy
description	Lung cancer is one of the most common tumors. There are 1.8 million new cases worldwide each year, accounting for about 13% of all new tumors. Lung cancer is the most important cause of cancer-related deaths. 1.4 million people die of lung cancer each year. This article uses artificial intelligence technology to analyze the pathology of hesperetin-derived small cell lung cancer under fiberoptic bronchoscopy. This article takes 48 lung slice samples as the research object. Among them, 36 cases of lung small cell carcinoma have history slices from Lhasa City Institute of Biology, the patient has complete cases, and the other 12 normal lung slices come from Xinjiang Biotechnology Laboratory. In this paper, the above-mentioned 36 lung cancer slices became the study group, and 12 normal slices became the reference group. This article presents a method for hesperetin-fiber bronchoscope to study the pathological mechanism of lung small cell carcinoma (H-FBS), which is used to study slices. The above-mentioned 48 samples were taken for slice observation. First, the 48 slices were technically tested by artificial intelligence fiber bronchoscope combined with hesperetin derivatives, and then the slice observation results were verified by CTC technology. In addition, in each step, the C5orf34 in the tissue is detected separately, which is beneficial to adjust the content of C5orf34 so that the treatment of lung cancer can control the development of lung cancer under fiberoptic bronchoscopy. Experimental results show that the diagnostic accuracy rate of this method is 97.9%, which is higher than that of lung biopsy (89%); compared with multiple CTC detection, the cost is low and the time is shor.
format	article
author	Xiaoli Zhang Ziying Yu
author_facet	Xiaoli Zhang Ziying Yu
author_sort	Xiaoli Zhang
title	Pathological analysis of hesperetin-derived small cell lung cancer by artificial intelligence technology under fiberoptic bronchoscopy
title_short	Pathological analysis of hesperetin-derived small cell lung cancer by artificial intelligence technology under fiberoptic bronchoscopy
title_full	Pathological analysis of hesperetin-derived small cell lung cancer by artificial intelligence technology under fiberoptic bronchoscopy
title_fullStr	Pathological analysis of hesperetin-derived small cell lung cancer by artificial intelligence technology under fiberoptic bronchoscopy
title_full_unstemmed	Pathological analysis of hesperetin-derived small cell lung cancer by artificial intelligence technology under fiberoptic bronchoscopy
title_sort	pathological analysis of hesperetin-derived small cell lung cancer by artificial intelligence technology under fiberoptic bronchoscopy
publisher	AIMS Press
publishDate	2021
url	https://doaj.org/article/ed8db61b85114d89af48218ec316d4ae
work_keys_str_mv	AT xiaolizhang pathologicalanalysisofhesperetinderivedsmallcelllungcancerbyartificialintelligencetechnologyunderfiberopticbronchoscopy AT ziyingyu pathologicalanalysisofhesperetinderivedsmallcelllungcancerbyartificialintelligencetechnologyunderfiberopticbronchoscopy
_version_	1718407683568041984

Pathological analysis of hesperetin-derived small cell lung cancer by artificial intelligence technology under fiberoptic bronchoscopy

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