ArticleZhongguo fei ai za zhi = Chinese journal of lung cancer2019
[Clinical Application of Artificial Intelligence Recognition Technology in the Diagnosis of Stage T1 Lung Cancer].
Article in Zhongguo fei ai za zhi = Chinese journal of lung cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 19 citations in OpenAlex.
- State-of-the-art artificial intelligence methods for pre-operative planning of cardiothoracic surgery and interventions: a narrative review.Journal of thoracic disease · 2025Review
- A Thorough Review of the Clinical Applications of Artificial Intelligence in Lung Cancer.Cancers · 2025Review
- Knowledge and Perception of the Use of AI and its Implementation in the Field of Radiology: Cross-Sectional Study.Journal of medical Internet research · 2023Observational
- Diabetic wounds and artificial intelligence: A mini-review.World journal of clinical cases · 2023Review
- Identification of pathological subtypes of early lung adenocarcinoma based on artificial intelligence parameters and CT signs.Bioscience reports · 2022Article
- Artificial neural network in the discrimination of lung cancer based on infrared spectroscopy.PloS one · 2022Article
- Artificial intelligence for early diagnosis of lung cancer through incidental nodule detection in low- and middle-income countries-acceleration during the COVID-19 pandemic but here to stay.American journal of cancer research · 2022Review
- Artificial Intelligence Evidence-Based Current Status and Potential for Lower Limb Vascular Management.Journal of personalized medicine · 2021Review
- Review
- Review
- Toward Systems Pathology for PTEN Diagnostics.Cold Spring Harbor perspectives in medicine · 2020Review
- Navigating patient journey in early diagnosis of lung cancer in India.Lung India : official organ of Indian Chest SocietyReview
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Authors and funding
6 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundLung cancer is the cancer with the highest morbidity and mortality at home and abroad at present. Using computed tomography (CT) to screen lung cancer nodules is a huge workload. To test the effect of artificial intelligence in automatic identification of lung cancer by using artificial intelligence to find the lung cancer nodules automatically in the chest CT of 1 mm and 5 mm thick.
methods5,000 cases of T1 stage lung cancer patients with 1 mm and 5 mm layer thickness were respectively labeled and learned by computer neural network, the algorithm of forming pulmonary nodules was carried out. 500 cases of chest CT in T1 stage lung cancer patients with 1 mm and 5 mm thickness were tested by artificial intelligence formation, and the sensitivity and specificity were compared with artificial reading.
resultsUsing artificial intelligence to read chest CT 500 in 5 mm, the sensitivity was 95.20%, the specificity was 93.20%, and the Kappa value of two times repeated read was 0.926,1. For 1 mm chest CT 500 cases, the sensitivity is 96.40%, the specificity is 95.60%, and the Kappa reads two times is 0.938,6. Compared with 5 doctors, the same CT sets with 1 mm thickness were read. The detection rates of artificial intelligence and artificial reading were similar to those of lung cancer nodules and negative control read films, and there was no significant difference between them. In the comparison of the same CT slices with 5 mm thickness, the number of detection of lung cancer nodules by artificial intelligence is better than that of artificial reading, and the sensitivity is higher, but the number of false messages is increased and the specificity is slightly worse.
conclusionsThe automatic learning of early lung cancer chest CT images by artificial intelligence can achieve high sensitivity and specificity of early lung cancer identification, and assist doctors in the diagnosis of lung cancer.
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