Can Artificial Intelligence Fix the Reproducibility Problem of Radiomics?-Reference-Cited by-同舟云学术

Can Artificial Intelligence Fix the Reproducibility Problem of Radiomics?

Published:2019-08 Issue:2 Volume:292 Page:374-375
ISSN:0033-8419
Container-title:Radiology
language:en
Short-container-title:Radiology

Author:

Park Chang Min¹^ORCID

Affiliation:

1. From the Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 03080, Korea.

Publisher

Radiological Society of North America (RSNA)

Subject

Radiology Nuclear Medicine and imaging

Link

http://pubs.rsna.org/doi/pdf/10.1148/radiol.2019191154

Reference6 articles.

1. Radiomics: Images Are More than Pictures, They Are Data

2. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

3. Radiomics: the bridge between medical imaging and personalized medicine

4. Impact of Reconstruction Algorithms on CT Radiomic Features of Pulmonary Tumors: Analysis of Intra- and Inter-Reader Variability and Inter-Reconstruction Algorithm Variability

5. Radiomics of CT Features May Be Nonreproducible and Redundant: Influence of CT Acquisition Parameters

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