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Quantitative assessment of AI-based chest CT lung nodule detection in lung cancer screening: future prospects and main challenges

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dc.contributor.author Исмаилова М.Х.
dc.date.accessioned 2022-12-13T10:06:28Z
dc.date.available 2022-12-13T10:06:28Z
dc.date.issued 2022-12
dc.identifier.uri http://repository.tma.uz/xmlui/handle/1/4984
dc.description.abstract Lung cancer is the most common cause of cancer-related death. It is known for being particularly aggressive. Early detection of asymptomatic lung cancer is crucial for optimal treatment, which can greatly increase patients' survival rates. Since the beginning of the twentieth century, the incidence in the population has increased several times. Its growth is especially pronounced in industrialized countries, where lung cancer ranks first in the structure of oncological morbidity. Lung cancer also ranks among the top three cancers in terms of incidence rates for both men and women. As the precursor, lung nodules are the main indication of lung cancer. Therefore, lung screening by CT exams has been recommended for identifying and characterizing nodules to detect early lung cancer. en_US
dc.publisher uINNOVATION-GLOBAL (Scientific Magazine of United Imaging Healthcare) en_US
dc.subject CT lung nodule, lung cancer en_US
dc.title Quantitative assessment of AI-based chest CT lung nodule detection in lung cancer screening: future prospects and main challenges en_US
dc.title.alternative Quantitative assessment of AI-based chest CT lung nodule detection in lung cancer screening: future prospects and main challenges en_US
dc.type Article en_US


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