Use Test of Automated Machine Learning in Cancer Diagnostics

Our aim is to investigate the added value of automated machine learning (AutoML) for potential future applications in cancer diagnostics. Using two important diagnostic questions, the non-invasive determination of IDH mutation status and ATRX status, we analyze whether it is possible to use AutoML t...

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Detalles Bibliográficos
Autores principales: Musigmann, Manfred, Nacul, Nabila Gala, Kasap, Dilek N., Heindel, Walter, Mannil, Manoj
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10378334/
https://www.ncbi.nlm.nih.gov/pubmed/37510059
http://dx.doi.org/10.3390/diagnostics13142315

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10378334/
https://www.ncbi.nlm.nih.gov/pubmed/37510059
http://dx.doi.org/10.3390/diagnostics13142315

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