Imaging biomarkers: Radiomics and the use of artificial intelligence in nuclear oncology
Nuclear Oncology: From Pathophysiology to Clinical Applications, Page: 411-427
2022
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Book Chapter Description
Medical imaging is moving toward automated systems and approaches capable of assisting and supporting medical decisions. For more than a decade, radiomics and artificial intelligence (AI) approaches have been widely explored. In particular, in oncology a considerable number of studies reported on biomarkers derived from computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). Lack of standardization and robust study design, variability in methodology, and incomplete reporting limit the comparison of results across studies and, consequently, clinical translation. In the present chapter, we describe the methodological steps of radiomics and AI-methods applied to imaging. Furthermore, the main clinical applications will be illustrated.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85153825555&origin=inward; http://dx.doi.org/10.1007/978-3-031-05494-5_89; https://link.springer.com/10.1007/978-3-031-05494-5_89; https://dx.doi.org/10.1007/978-3-031-05494-5_89; https://link.springer.com/referenceworkentry/10.1007/978-3-031-05494-5_89
Springer Science and Business Media LLC
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