Multiclass risk models for ovarian malignancy: an illustration of prediction uncertainty due to the choice of algorithm

BACKGROUND: Assessing malignancy risk is important to choose appropriate management of ovarian tumors. We compared six algorithms to estimate the probabilities that an ovarian tumor is benign, borderline malignant, stage I primary invasive, stage II-IV primary invasive, or secondary metastatic. METH...

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Detalles Bibliográficos
Autores principales: Ledger, Ashleigh, Ceusters, Jolien, Valentin, Lil, Testa, Antonia, Van Holsbeke, Caroline, Franchi, Dorella, Bourne, Tom, Froyman, Wouter, Timmerman, Dirk, Van Calster, Ben
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10668424/
https://www.ncbi.nlm.nih.gov/pubmed/38001421
http://dx.doi.org/10.1186/s12874-023-02103-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10668424/
https://www.ncbi.nlm.nih.gov/pubmed/38001421
http://dx.doi.org/10.1186/s12874-023-02103-3

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