Literature DB >> 21097080

Secondary use of EHR data for correlated comorbidity prevalence estimate.

Srdjan B Stakic1, Sanja Tasic.   

Abstract

Comorbidity is quite common in the medical practice. In this article we explore a way to use anonymized Electronic Health Records (EHR) data in order to derive correlations, evidence based likelihood of comorbidities manifestation within the EHR patients population. The ultimate goal is to present the information to the health care provider at the moment when a new diagnosis is entered for the patient, thus increasing health care provider's attention to possible problems, even if they are at sub-clinical or asymptomatic stage.

Entities:  

Mesh:

Year:  2010        PMID: 21097080     DOI: 10.1109/IEMBS.2010.5627691

Source DB:  PubMed          Journal:  Annu Int Conf IEEE Eng Med Biol Soc        ISSN: 2375-7477


  3 in total

1.  Feature extraction for phenotyping from semantic and knowledge resources.

Authors:  Wenxin Ning; Stephanie Chan; Andrew Beam; Ming Yu; Alon Geva; Katherine Liao; Mary Mullen; Kenneth D Mandl; Isaac Kohane; Tianxi Cai; Sheng Yu
Journal:  J Biomed Inform       Date:  2019-02-07       Impact factor: 6.317

2.  Toward high-throughput phenotyping: unbiased automated feature extraction and selection from knowledge sources.

Authors:  Sheng Yu; Katherine P Liao; Stanley Y Shaw; Vivian S Gainer; Susanne E Churchill; Peter Szolovits; Shawn N Murphy; Isaac S Kohane; Tianxi Cai
Journal:  J Am Med Inform Assoc       Date:  2015-04-29       Impact factor: 4.497

3.  Surrogate-assisted feature extraction for high-throughput phenotyping.

Authors:  Sheng Yu; Abhishek Chakrabortty; Katherine P Liao; Tianrun Cai; Ashwin N Ananthakrishnan; Vivian S Gainer; Susanne E Churchill; Peter Szolovits; Shawn N Murphy; Isaac S Kohane; Tianxi Cai
Journal:  J Am Med Inform Assoc       Date:  2017-04-01       Impact factor: 4.497

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.