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Machine Learning Tools for Image-Based Glioma Grading and the Quality of Their Reporting: Challenges and Opportunities
SIMPLE SUMMARY: Despite their prevalence in research, ML tools that can predict glioma grade from medical images have yet to be incorporated clinically. The reporting quality of ML glioma grade prediction studies is below 50% according to TRIPOD—limiting model reproducibility and, thus, clinical tra...
Autores principales: | Merkaj, Sara, Bahar, Ryan C., Zeevi, Tal, Lin, MingDe, Ikuta, Ichiro, Bousabarah, Khaled, Cassinelli Petersen, Gabriel I., Staib, Lawrence, Payabvash, Seyedmehdi, Mongan, John T., Cha, Soonmee, Aboian, Mariam S. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9179416/ https://www.ncbi.nlm.nih.gov/pubmed/35681603 http://dx.doi.org/10.3390/cancers14112623 |
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