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Lung cancer is one of the leading cause of cancer related death in China. Lung cancer screening with low-dose computed tomography was considered as a better approach than radiography. However, the role of Lung cancer screening with Low-dose CT (LDCT) among Chinese people remains unclear. With rapid development of artificial intelligence (AI),the application of AI in detection and diagnosis of diseases has become research focus. Moreover, patients' psychological status also plays an important role in diagnosis and treatment.
This study focuses on detection and natural history management of lung nodule and lung cancer with AI assisted chest CT among people living in North China, and aims to investigate epidemiological results, patients' medical records and social psychological status.
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Lu'an Municipal Hospital and North China Petroleum Bureau General Hospital initialed the lung cancer screening by LDCT a few years ago. People living in North China who are administrated by these hospitals routinely took a chest CT every year. This study is to the best of our knowledge the first one designed to combine lung nodule and lung cancer screening with the application of artificial intelligence in China.
Methods: Firstly, the study acquires epidemiological, medical information and psychological status of people recruited, and investigates the data acquired from past several years of CT scans using AI to develop a model for lung nodule detection. Secondly, evaluating the performance of models and apply it to analyse the CT scans from the North China population recruited. Thirdly, improving the model and adding function for lung nodule prediction of natural history and probability of malignancy.
Aims: To depict the epidemiological results about the incidence of lung nodules and lung cancer in North China population; To evaluate association between people 's epidemiological, medical and psychological profiles and incidence, diagnosis and treatment of lung nodule; To develop an artificial intelligence assisted lung nodule diagnosis and management software to assist strategies of CT screening.
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5,000 participants in 1 patient group
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Jun J Wang, MM; Feng F Yang, MD
Data sourced from clinicaltrials.gov
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