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Advancing radiomics research translation through a public database.

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Title: Advancing radiomics research translation through a public database.
Authors: Ko, Hyun Soo1,2,3 (AUTHOR) hyun.ko@petermac.org
Source: European Radiology. Jan2024, Vol. 34 Issue 1, p433-435. 3p.
Subjects: Radiomics, Databases, Scientific knowledge, Texture analysis (Image processing), Computer-assisted image analysis (Medicine)
Abstract: Radiomics, a technique that involves analyzing medical imaging characteristics, has gained significant interest among researchers in recent years. However, the translation of radiomics into clinical practice has been hindered by challenges in reproducibility. A recent study analyzed the reproducibility of radiomic research studies published in 2021 and 2022 and found that only a small fraction of studies shared their code or data. To address this issue, an open-source repository has been established to provide easy access to radiomics studies and encourage collaboration and replication. The repository aims to promote inclusivity, enhance researcher diversity and collaboration, facilitate replication and validation, ensure long-term data preservation, and reduce research costs. However, it is important to address critical factors such as user-friendly interfaces, quality control measures, and accuracy to maintain the repository's usefulness and utility. The repository has the potential to become a valuable resource for the radiomics research community and contribute to the successful integration of radiomics into clinical practice. [Extracted from the article]
Copyright of European Radiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Advancing radiomics research translation through a public database.
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  Data: <searchLink fieldCode="DE" term="%22Radiomics%22">Radiomics</searchLink><br /><searchLink fieldCode="DE" term="%22Databases%22">Databases</searchLink><br /><searchLink fieldCode="DE" term="%22Scientific+knowledge%22">Scientific knowledge</searchLink><br /><searchLink fieldCode="DE" term="%22Texture+analysis+%28Image+processing%29%22">Texture analysis (Image processing)</searchLink><br /><searchLink fieldCode="DE" term="%22Computer-assisted+image+analysis+%28Medicine%29%22">Computer-assisted image analysis (Medicine)</searchLink>
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  Data: Radiomics, a technique that involves analyzing medical imaging characteristics, has gained significant interest among researchers in recent years. However, the translation of radiomics into clinical practice has been hindered by challenges in reproducibility. A recent study analyzed the reproducibility of radiomic research studies published in 2021 and 2022 and found that only a small fraction of studies shared their code or data. To address this issue, an open-source repository has been established to provide easy access to radiomics studies and encourage collaboration and replication. The repository aims to promote inclusivity, enhance researcher diversity and collaboration, facilitate replication and validation, ensure long-term data preservation, and reduce research costs. However, it is important to address critical factors such as user-friendly interfaces, quality control measures, and accuracy to maintain the repository's usefulness and utility. The repository has the potential to become a valuable resource for the radiomics research community and contribute to the successful integration of radiomics into clinical practice. [Extracted from the article]
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  Data: <i>Copyright of European Radiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s00330-023-10284-0
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              Text: Jan2024
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