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Assessing the predictive accuracy of lung cancer, metastases, and benign lesions using an artificial intelligence-driven computer aided diagnosis system
Author(s) -
Kunwei Li,
Kunfeng Liu,
Yinghua Zhong,
Mingzhu Liang,
Peixin Qin,
Haijun Li,
Rongguo Zhang,
Shaolin Li,
Xueguo Liu
Publication year - 2021
Publication title -
quantitative imaging in medicine and surgery
Language(s) - English
Resource type - Journals
eISSN - 2223-4306
pISSN - 2223-4292
DOI - 10.21037/qims-20-1314
Subject(s) - medicine , malignancy , radiology , lung , lung cancer , lesion , diagnostic accuracy , pathology
Artificial intelligence (AI) products have been widely used for the clinical detection of primary lung tumors. However, their performance and accuracy in risk prediction for metastases or benign lesions remain underexplored. This study evaluated the accuracy of an AI-driven commercial computer-aided detection (CAD) product (InferRead CT Lung Research, ICLR) in malignancy risk prediction using a real-world database.

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