title: Knowledge-analytics synergy in Clinical Decision Support.
abstract: Clinical Decision Support (CDS) systems hold tremendous potential for improving patient care. Most existing systems are knowledge-based tools that rely on relatively simple rules. More recent approaches rely on analytics techniques to automatically mine EHR data to reveal meaningful insights. Here, we propose the Knowledge-Analytics Synergy paradigm for CDS, in which we synergistically combine existing relevant knowledge with analytics applied to EHR data. We propose a framework for implementing such a paradigm and demonstrate its principles over real-world clinical and genomic data of hypertensive patients.
authors.affiliation: Haifa University, Mount Carmel, Haifa, Israel. noams@il.ibm.com
authors.forename: Noam
authors.initials: N
authors.lastname: Slonim
authors.forename: Boaz
authors.initials: B
authors.lastname: Carmeli
authors.forename: Abigail
authors.initials: A
authors.lastname: Goldsteen
authors.forename: Oliver
authors.initials: O
authors.lastname: Keller
authors.forename: Carmel
authors.initials: C
authors.lastname: Kent
authors.forename: Ruty
authors.initials: R
authors.lastname: Rinott
mesh_terms: D001185:Artificial Intelligence; D057225:Data Mining / Q000379:methods*; D020000:Decision Support Systems, Clinical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D057286:Electronic Health Records; D055991:Health Records, Personal; D006801:Humans; D006973:Hypertension / Q000175:diagnosis*; D051188:Knowledge Bases