September 19, 2024Open Access

Artificial intelligence-assisted quantitative CT parameters in predicting the degree of risk of solitary pulmonary nodules

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Abstract

Artificial intelligence (AI) shows promise for evaluating solitary pulmonary nodules (SPNs) on computed tomography (CT). Accurately determining cancer invasiveness can guide treatment. We aimed to investigate quantitative CT parameters for invasiveness prediction.

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Authors

Long Jiang

Yang Zhou

Miao Wang

Journals

Annals of Medicine

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Institutions

Shanghai Jiao Tong University

Shanghai Chest Hospital

Zhengzhou People's Hospital

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Artificial intelligence-assisted quantitative CT parameters in predicting the degree of risk of solitary pulmonary nodules

Key Points

Abstract

Citation Network

Connected Papers

Discussion

Authors

Journals

Actions

Institutions

References and Citations

Citation Network

Connected Papers

Discussion

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