Machine Learning Lead Optimisation: A Short Communication on Prospective Versus Retrospective Performance
DOI:
https://doi.org/10.5281/zenodo.22649052Keywords:
Machine Learning Lead Optimisation; Translational medicine, Evidence synthesis; Clinical implementation; Health services researchAbstract
Machine Learning Lead Optimisation is an area of active development in translational medicine, with evidence that has
accumulated unevenly across its component questions. We review the current evidence base for machine learning lead
optimisation, spanning analytical, clinical, implementation, governance, and economic dimensions, focusing on where practice
has converged and where it continues to vary, and set out the practical considerations relevant to a service considering its
adoption. We conclude that selective, context-specific use is best supported by the evidence currently available, rather than
uniform adoption or avoidance.
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