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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| Format: | Article |
| Language: | English |
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AIMS Press
2021-09-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2021423?viewType=HTML |
| _version_ | 1818433914682736640 |
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| author | Xiaoli Zhang Ziying Yu |
| author_facet | Xiaoli Zhang Ziying Yu |
| author_sort | Xiaoli Zhang |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-14T16:28:40Z |
| format | Article |
| id | doaj.art-ed8db61b85114d89af48218ec316d4ae |
| institution | Directory Open Access Journal |
| issn | 1551-0018 |
| language | English |
| last_indexed | 2024-12-14T16:28:40Z |
| publishDate | 2021-09-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj.art-ed8db61b85114d89af48218ec316d4ae2022-12-21T22:54:38ZengAIMS PressMathematical Biosciences and Engineering1551-00182021-09-011868538855810.3934/mbe.2021423Pathological analysis of hesperetin-derived small cell lung cancer by artificial intelligence technology under fiberoptic bronchoscopyXiaoli Zhang 0Ziying Yu11. Department of Pathology, The First Affiliated Hospital of University of South China, Hengyang 421001, China2. Department of Emergency, The First Affiliated Hospital of University of South China, Hengyang 421001, ChinaLung 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.https://www.aimspress.com/article/doi/10.3934/mbe.2021423?viewType=HTMLhesperetin derivativeslung small cell carcinomacirculating cell detection technologyfiberoptic bronchoscopy |
| spellingShingle | Xiaoli Zhang Ziying Yu Pathological analysis of hesperetin-derived small cell lung cancer by artificial intelligence technology under fiberoptic bronchoscopy Mathematical Biosciences and Engineering hesperetin derivatives lung small cell carcinoma circulating cell detection technology fiberoptic bronchoscopy |
| title | 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_short | 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 |
| topic | hesperetin derivatives lung small cell carcinoma circulating cell detection technology fiberoptic bronchoscopy |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2021423?viewType=HTML |
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