Cargando…
Development and validation of multivariable machine learning algorithms to predict risk of cancer in symptomatic patients referred urgently from primary care: a diagnostic accuracy study
OBJECTIVES: To develop and validate tests to assess the risk of any cancer for patients referred to the NHS Urgent Suspected Cancer (2-week wait, 2WW) clinical pathways. SETTING: Primary and secondary care, one participating regional centre. PARTICIPANTS: Retrospective analysis of data from 371 799...
Autores principales: | Savage, Richard, Messenger, Mike, Neal, Richard D, Ferguson, Rosie, Johnston, Colin, Lloyd, Katherine L, Neal, Matthew D, Sansom, Nigel, Selby, Peter, Sharma, Nisha, Shinkins, Bethany, Skinner, Jim R, Tully, Giles, Duffy, Sean, Hall, Geoff |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8977764/ https://www.ncbi.nlm.nih.gov/pubmed/35365520 http://dx.doi.org/10.1136/bmjopen-2021-053590 |
Ejemplares similares
-
Trends and variation in urgent referrals for suspected cancer 2009/2010–2019/2020
por: Smith, Lesley, et al.
Publicado: (2021) -
An exploratory assessment of the impact of a novel risk assessment test on breast cancer clinic waiting times and workflow: a discrete event simulation model
por: Smith, Alison F., et al.
Publicado: (2022) -
Diagnosing myeloma in general practice: how might earlier diagnosis be achieved?
por: Smith, Lesley, et al.
Publicado: (2022) -
Development and Internal Validation of a Risk Prediction Model to Identify Myeloma Based on Routine Blood Tests: A Case-Control Study
por: Smith, Lesley, et al.
Publicado: (2023) -
The Character Strengths Response: An Urgent Call to Action
por: Mayerson, Neal H.
Publicado: (2020)