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            Brain and Human Body Modelling 2021

            Selected papers presented at 2021 BHBM Conference at Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital

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            Contributor(s)
            Makarov, Sergey (editor)
            Noetscher, Gregory (editor)
            Nummenmaa, Aapo (editor)
            Language
            English
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            Abstract
            This open access book describes modern applications of computational human modelling to advance neurology, cancer treatment, and radio-frequency studies including regulatory, safety, and wireless communication fields. Readers working on any application that may expose human subjects to electromagnetic radiation will benefit from this book’s coverage of the latest models and techniques available to assess a given technology’s safety and efficacy in a timely and efficient manner. This is an Open Access book.
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/169211
            Keywords
            Electromagnetic Modeling for Electrical and Biological Systems; Anatomical Models for Radiation Dosimetry; Computational Human Phantoms; Computational Human Models; Electromagnetic safety and exposure evaluations; thema EDItEUR::M Medicine and Nursing::MQ Nursing and ancillary services::MQW Biomedical engineering; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFN Microwave technology; thema EDItEUR::P Mathematics and Science::PH Physics::PHV Applied physics::PHVN Biophysics
            DOI
            10.1007/978-3-031-15451-5
            ISBN
            9783031154515
            Publisher
            Springer Nature
            Publisher website
            http://www.springernature.com/oabooks
            Publication date and place
            Cham, 2023
            Imprint
            Springer
            Pages
            172
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            Credits


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              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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