Diagnostic Accuracy and Performance of Artificial Intelligence in Detecting Lung Nodules in Patients With Complex Lung Disease: A Noninferiority Study.
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| Title: | Diagnostic Accuracy and Performance of Artificial Intelligence in Detecting Lung Nodules in Patients With Complex Lung Disease: A Noninferiority Study. |
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| Authors: | Abadia AF; Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC., Yacoub B; Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC., Stringer N; Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC., Snoddy M; Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC., Kocher M; Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC., Schoepf UJ; Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC., Aquino GJ; Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC., Kabakus I; Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC., Dargis D; Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC., Hoelzer P; Siemens Healthineers, Erlangen, Germany., Sperl JI; Siemens Healthineers, Erlangen, Germany., Sahbaee P; Siemens Healthineers, Erlangen, Germany., Vingiani V; Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC.; U.O.C. Radiologia, Ospedali Riuniti 'Area Peninsola Sorrentina,' P.O. Sorrento, Italy., Mercer M; Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC., Burt JR; Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC. |
| Source: | Journal of thoracic imaging [J Thorac Imaging] 2022 May 01; Vol. 37 (3), pp. 154-161. Date of Electronic Publication: 2021 Aug 12. |
| Publication Type: | Equivalence Trial; Journal Article |
| Journal Info: | Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 8606160 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1536-0237 (Electronic) Linking ISSN: 08835993 NLM ISO Abbreviation: J Thorac Imaging Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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