Literature DB >> 22874282

Knowledge-analytics synergy in Clinical Decision Support.

Noam Slonim1, Boaz Carmeli, Abigail Goldsteen, Oliver Keller, Carmel Kent, Ruty Rinott.   

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.

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Year:  2012        PMID: 22874282

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  3 in total

Review 1.  A review of analytics and clinical informatics in health care.

Authors:  Allan F Simpao; Luis M Ahumada; Jorge A Gálvez; Mohamed A Rehman
Journal:  J Med Syst       Date:  2014-04-03       Impact factor: 4.460

2.  Using a machine learning approach to predict mortality in critically ill influenza patients: a cross-sectional retrospective multicentre study in Taiwan.

Authors:  Chien-An Hu; Chia-Ming Chen; Yen-Chun Fang; Shinn-Jye Liang; Hao-Chien Wang; Wen-Feng Fang; Chau-Chyun Sheu; Wann-Cherng Perng; Kuang-Yao Yang; Kuo-Chin Kao; Chieh-Liang Wu; Chwei-Shyong Tsai; Ming-Yen Lin; Wen-Cheng Chao
Journal:  BMJ Open       Date:  2020-02-25       Impact factor: 2.692

Review 3.  Clinically Excellent Use of the Electronic Health Record: Review.

Authors:  Leah Wolfe; Margaret Smith Chisolm; Fuad Bohsali
Journal:  JMIR Hum Factors       Date:  2018-10-05
  3 in total

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