title: ASCOT: a text mining-based web-service for efficient search and assisted creation of clinical trials.
abstract: Clinical trials are mandatory protocols describing medical research on humans and among the most valuable sources of medical practice evidence. Searching for trials relevant to some query is laborious due to the immense number of existing protocols. Apart from search, writing new trials includes composing detailed eligibility criteria, which might be time-consuming, especially for new researchers. In this paper we present ASCOT, an efficient search application customised for clinical trials. ASCOT uses text mining and data mining methods to enrich clinical trials with metadata, that in turn serve as effective tools to narrow down search. In addition, ASCOT integrates a component for recommending eligibility criteria based on a set of selected protocols.
authors.affiliation: National Centre for Text Mining & School of Computer Science, The University of Manchester, Manchester M1 7DN, UK. Ioannis.Korkontzelos@manchester.ac.uk
authors.forename: Ioannis
authors.initials: I
authors.lastname: Korkontzelos
authors.forename: Tingting
authors.initials: T
authors.lastname: Mu
authors.forename: Sophia
authors.initials: S
authors.lastname: Ananiadou
mesh_terms: D000465:Algorithms; D002986:Clinical Trials as Topic; D016000:Cluster Analysis; D003626:Data Display; D057225:Data Mining; D016208:Databases, Factual; D003658:Decision Making, Computer-Assisted; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet; D009323:Natural Language Processing; D039061:Systematized Nomenclature of Medicine; D017432:Unified Medical Language System; D006113:United Kingdom; D014584:User-Computer Interface