Business Analytics and Grammatical Evolution for the Prediction of Patient Recruitment in Multicentre Clinical Trials

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@InCollection{Borlikova:2018:hbge,

• author = "Gilyana Borlikova and Louis Smith and Michael Phillips and Michael O'Neill",
• title = "Business Analytics and Grammatical Evolution for the Prediction of Patient Recruitment in Multicentre Clinical Trials",
• booktitle = "Handbook of Grammatical Evolution",
• publisher = "Springer",
• year = "2018",
• editor = "Conor Ryan and Michael O'Neill and J. J. Collins",
• chapter = "19",
• pages = "461--486",
• keywords = "genetic algorithms, genetic programming, Grammatical Evolution",
• isbn13 = "978-3-319-78716-9",
• DOI = "doi:10.1007/978-3-319-78717-6_19",
• 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.",
• notes = "Part of \cite{Ryan:2018:hbge}",

}

Genetic Programming entries for Gilyana Borlikova Louis Smith Michael Phillips Michael O'Neill

Citations