Business Analytics and Grammatical Evolution for the Prediction of Patient Recruitment in Multicentre Clinical Trials
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- @InCollection{Borlikova:2018:hbge,
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author = "Gilyana Borlikova and Louis Smith and
Michael Phillips and Michael O'Neill",
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title = "Business Analytics and Grammatical Evolution for the
Prediction of Patient Recruitment in Multicentre
Clinical Trials",
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booktitle = "Handbook of Grammatical Evolution",
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publisher = "Springer",
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year = "2018",
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editor = "Conor Ryan and Michael O'Neill and J. J. Collins",
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chapter = "19",
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pages = "461--486",
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keywords = "genetic algorithms, genetic programming, Grammatical
Evolution",
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isbn13 = "978-3-319-78716-9",
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DOI = "doi:10.1007/978-3-319-78717-6_19",
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abstract = "For a drug to be approved for human use, its safety
and efficacy need to be evidenced through clinical
trials. Optimisation of patient recruitment is an
active area of business interest for pharma and
contract research organisations (CRO) conducting
clinical trials. The healthcare industry and CROs are
gradually starting to adapt business analytics
techniques to improve processes and help boost
performance. Development of methods able to predict at
the outset which prospective investigators/sites will
succeed in patient recruitment can provide powerful
tools for this business problem. In this chapter we
describe the application of Grammatical Evolution to
the prediction of patient recruitment in multicentre
clinical trials.",
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notes = "Part of \cite{Ryan:2018:hbge}",
- }
Genetic Programming entries for
Gilyana Borlikova
Louis Smith
Michael Phillips
Michael O'Neill
Citations