Assessing eligibility for lung cancer screening using parsimonious ensemble machine learning models: A development and validation study is a research paper published in PLoS Medicine (2023). On theSindex it has a DataRank of 0. It has been cited 27 times.
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Wellcome Trust
Grant: 222890/Z/21/Z
National Science Foundation
Grant: 1722516
SCH: INT: Personalized Real-Time Learning of Optimal Diagnostic Tests using Multi-Modal Clinical Data
Medical Research Council
Grant: MR/T02481X/1
Derivation and validation of a novel model incorporating PET-CT for predicting malignancy in screen detected lung nodules - The PRECISE Study
Medical Research Council
Grant: MR/W025051/1
Mapping longitudinal squamous cell lung cancer pathogenesis in pursuit of a preventative therapy
Cancer Research UK
Grant: EDDCPGM\100002
Cancer Research UK
Grant: 28706
Wellcome Trust
Grant: 222890
Personalising lung cancer screening with tumour growth dynamics
Wellcome Trust
FWCI
4.73
Citation Percentile
1.0%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals