Clinical utility of an artificial intelligence radiomics-based tool for risk stratification of pulmonary nodules.

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Bibliographic Details
Title: Clinical utility of an artificial intelligence radiomics-based tool for risk stratification of pulmonary nodules.
Authors: Kim RY; Division of Pulmonary, Allergy and Critical Care, Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA., Yee C; NYU Langone Health, New York City, NY, USA., Zeb S; Division of Pulmonary, Allergy and Critical Care, Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA., Steltz J; Division of Pulmonary, Allergy and Critical Care, Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA., Vickers AJ; Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, NY, USA., Rendle KA; Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA., Mitra N; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA., Pickup LC; Optellum Ltd, Oxford, UK., DiBardino DM; Division of Pulmonary, Allergy and Critical Care, Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA., Vachani A; Division of Pulmonary, Allergy and Critical Care, Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Source: JNCI cancer spectrum [JNCI Cancer Spectr] 2024 Sep 02; Vol. 8 (5).
Publication Type: Journal Article
Journal Info: Publisher: Oxford University Press Country of Publication: England NLM ID: 101721827 Publication Model: Print Cited Medium: Internet ISSN: 2515-5091 (Electronic) Linking ISSN: 25155091 NLM ISO Abbreviation: JNCI Cancer Spectr Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:2515-5091
DOI:10.1093/jncics/pkae086