Cargando…
Protocol for a systematic review on the methodological and reporting quality of prediction model studies using machine learning techniques
INTRODUCTION: Studies addressing the development and/or validation of diagnostic and prognostic prediction models are abundant in most clinical domains. Systematic reviews have shown that the methodological and reporting quality of prediction model studies is suboptimal. Due to the increasing availa...
Autores principales: | Andaur Navarro, Constanza L, Damen, Johanna A A G, Takada, Toshihiko, Nijman, Steven W J, Dhiman, Paula, Ma, Jie, Collins, Gary S, Bajpai, Ram, Riley, Richard D, Moons, Karel GM, Hooft, Lotty |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7661369/ https://www.ncbi.nlm.nih.gov/pubmed/33177137 http://dx.doi.org/10.1136/bmjopen-2020-038832 |
Ejemplares similares
-
Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review
por: Andaur Navarro, Constanza L, et al.
Publicado: (2021) -
Completeness of reporting of clinical prediction models developed using supervised machine learning: a systematic review
por: Andaur Navarro, Constanza L., et al.
Publicado: (2022) -
Methodological conduct of prognostic prediction models developed using machine learning in oncology: a systematic review
por: Dhiman, Paula, et al.
Publicado: (2022) -
Reporting of prognostic clinical prediction models based on machine learning methods in oncology needs to be improved
por: Dhiman, Paula, et al.
Publicado: (2021) -
Risk of bias of prognostic models developed using machine learning: a systematic review in oncology
por: Dhiman, Paula, et al.
Publicado: (2022)