Cargando…
Machine Learning in Colorectal Cancer Risk Prediction from Routinely Collected Data: A Review
The inclusion of machine-learning-derived models in systematic reviews of risk prediction models for colorectal cancer is rare. Whilst such reviews have highlighted methodological issues and limited performance of the models included, it is unclear why machine-learning-derived models are absent and...
Autores principales: | Burnett, Bruce, Zhou, Shang-Ming, Brophy, Sinead, Davies, Phil, Ellis, Paul, Kennedy, Jonathan, Bandyopadhyay, Amrita, Parker, Michael, Lyons, Ronan A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9858109/ https://www.ncbi.nlm.nih.gov/pubmed/36673111 http://dx.doi.org/10.3390/diagnostics13020301 |
Ejemplares similares
-
Record linkage to enhance consented cohort and routinely collected health data from a UK birth cohort
por: Tingay, Karen Susan, et al.
Publicado: (2019) -
Proton pump inhibitors and dementia risk: Evidence from a cohort study using linked routinely collected national health data in Wales, UK
por: Cooksey, Roxanne, et al.
Publicado: (2020) -
Health and household environment factors linked with early alcohol use in adolescence: a record-linked, data-driven, longitudinal cohort study
por: Bandyopadhyay, Amrita, et al.
Publicado: (2022) -
Characteristics of Children Prescribed Antipsychotics: Analysis of Routinely Collected Data
por: Brophy, Sinead, et al.
Publicado: (2018) -
Predicting Hospital Readmission for Campylobacteriosis from Electronic Health Records: A Machine Learning and Text Mining Perspective
por: Zhou, Shang-Ming, et al.
Publicado: (2022)