Artificial intelligence methods applied to longitudinal data from electronic health records for prediction of cancer: a scoping review

Artificial intelligence methods applied to longitudinal data from electronic health records for prediction of cancer: a scoping review

Abstract Background Early detection and diagnosis of cancer are vital to improving outcomes for patients. Artificial intelligence (AI) models have shown promise in the early detection and diagnosis of cancer, but there is limited evidence on methods that fully exploit the longitudinal data stored wi...

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Bibliographic Details
Main Authors: Victoria Moglia, Owen Johnson, Gordon Cook, Marc de Kamps, Lesley Smith
Format: Article
Language:English
Published: BMC 2025-01-01
Series:BMC Medical Research Methodology
Subjects:
Machine learning
Health data
Longitudinal data
Cancer
Time-series
Temporal
Online Access:https://doi.org/10.1186/s12874-025-02473-w
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https://doi.org/10.1186/s12874-025-02473-w

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