Reproducibility of Deep Learning Algorithms Developed for Medical Imaging Analysis: A Systematic Review
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology
Link
https://link.springer.com/content/pdf/10.1007/s10278-023-00870-5.pdf
Reference23 articles.
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3. Oppenheimer J, Lüken S, Hamm B, Niehues SM. A Prospective Approach to Integration of AI Fracture Detection Software in Radiographs into Clinical Workflow. Life. 2023;13. https://doi.org/10.3390/life13010223
4. Arbabshirani MR, Fornwalt BK, Mongelluzzo GJ, Suever JD, Geise BD, Patel AA, et al. Advanced machine learning in action: identification of intracranial hemorrhage on computed tomography scans of the head with clinical workflow integration. NPJ Digit Med. 2018;1: 9.
5. Akkus Z, Cai J, Boonrod A, Zeinoddini A, Weston AD, Philbrick KA, et al. A Survey of Deep-Learning Applications in Ultrasound: Artificial Intelligence-Powered Ultrasound for Improving Clinical Workflow. J Am Coll Radiol. 2019;16: 1318–1328.
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