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Identifying clinically applicable machine learning algorithms for glioma segmentation: recent advances and discoveries
BACKGROUND: While there are innumerable machine learning (ML) research algorithms used for segmentation of gliomas, there is yet to be a US FDA cleared product. The aim of this study is to explore the systemic limitations of research algorithms that have prevented translation from concept to product...
Autores principales: | Tillmanns, Niklas, Lum, Avery E, Cassinelli, Gabriel, Merkaj, Sara, Verma, Tej, Zeevi, Tal, Staib, Lawrence, Subramanian, Harry, Bahar, Ryan C, Brim, Waverly, Lost, Jan, Jekel, Leon, Brackett, Alexandria, Payabvash, Sam, Ikuta, Ichiro, Lin, MingDe, Bousabarah, Khaled, Johnson, Michele H, Cui, Jin, Malhotra, Ajay, Omuro, Antonio, Turowski, Bernd, Aboian, Mariam S |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9446682/ https://www.ncbi.nlm.nih.gov/pubmed/36071926 http://dx.doi.org/10.1093/noajnl/vdac093 |
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