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        Evidence-based Positron Emission Tomography

        Summary of Recent Meta-analyses on PET

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        Contributor(s)
        Treglia, Giorgio (editor)
        Giovanella, Luca (editor)
        Language
        English
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        Abstract
        This open access book summarizes the findings of recent evidence-based articles (meta-analyses) on the use of positron emission tomography (PET) for various clinical indications. It is divided into five main sections, starting with an introduction to PET and meta-analysis. In turn, the second part addresses evidence-based PET in oncology, providing a broad overview of its use for different types of tumours. The remaining sections are focused on the use of PET in cardiology, in infectious and inflammatory diseases, and in neurology, respectively. Given its scope and the wealth of information it provides, the book will be an invaluable tool for clinicians with various specialties, as well as international scientific societies interested to the recent evidence-based data about PET.
        URI
        https://library.oapen.org/handle/20.500.12657/39988
        Keywords
        Nuclear Medicine; Diagnostic Radiology; Oncology; Cardiology; Neurology; Endocrinology; Radiology; Internal Medicine; Open Access; Meta-analysis; Diagnosis; Tumor; Infection; Nuclear medicine; Cardiovascular medicine; Neurology & clinical neurophysiology
        DOI
        10.1007/978-3-030-47701-1
        Publisher
        Springer Nature
        Publisher website
        https://www.springernature.com/gp/products/books
        Publication date and place
        2020
        Imprint
        Springer
        Classification
        Nuclear medicine
        Medical imaging: radiology
        Oncology
        Cardiovascular medicine
        Neurology and clinical neurophysiology
        Endocrinology
        Pages
        143
        Rights
        http://creativecommons.org/licenses/by/4.0/
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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