Literature DB >> 24788272

Mining the electronic health record for disease knowledge.

Elizabeth S Chen1, Indra Neil Sarkar.   

Abstract

The growing amount and availability of electronic health record (EHR) data present enhanced opportunities for discovering new knowledge about diseases. In the past decade, there has been an increasing number of data and text mining studies focused on the identification of disease associations (e.g., disease-disease, disease-drug, and disease-gene) in structured and unstructured EHR data. This chapter presents a knowledge discovery framework for mining the EHR for disease knowledge and describes each step for data selection, preprocessing, transformation, data mining, and interpretation/validation. Topics including natural language processing, standards, and data privacy and security are also discussed in the context of this framework.

Entities:  

Mesh:

Year:  2014        PMID: 24788272     DOI: 10.1007/978-1-4939-0709-0_15

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  13 in total

Review 1.  Aspiring to Unintended Consequences of Natural Language Processing: A Review of Recent Developments in Clinical and Consumer-Generated Text Processing.

Authors:  D Demner-Fushman; N Elhadad
Journal:  Yearb Med Inform       Date:  2016-11-10

Review 2.  Electronic Health Records: Then, Now, and in the Future.

Authors:  R S Evans
Journal:  Yearb Med Inform       Date:  2016-05-20

3.  Natural language processing of symptoms documented in free-text narratives of electronic health records: a systematic review.

Authors:  Theresa A Koleck; Caitlin Dreisbach; Philip E Bourne; Suzanne Bakken
Journal:  J Am Med Inform Assoc       Date:  2019-04-01       Impact factor: 4.497

4.  Free-Text Computerized Provider Order Entry Orders Used as Workaround for Communicating Medication Information.

Authors:  Swaminathan Kandaswamy; Joanna Grimes; Daniel Hoffman; Jenna Marquard; Raj M Ratwani; Aaron Z Hettinger
Journal:  J Patient Saf       Date:  2021-12-17       Impact factor: 2.243

5.  Robust clinical marker identification for diabetic kidney disease with ensemble feature selection.

Authors:  Xing Song; Lemuel R Waitman; Yong Hu; Alan S L Yu; David C Robbins; Mei Liu
Journal:  J Am Med Inform Assoc       Date:  2019-03-01       Impact factor: 4.497

Review 6.  Informatics Solutions for Application of Decision-Making Skills.

Authors:  Christine W Nibbelink; Janay R Young; Jane M Carrington; Barbara B Brewer
Journal:  Crit Care Nurs Clin North Am       Date:  2018-04-04       Impact factor: 1.326

7.  Mining and Visualizing Family History Associations in the Electronic Health Record: A Case Study for Pediatric Asthma.

Authors:  Elizabeth S Chen; Genevieve B Melton; Richard C Wasserman; Paul T Rosenau; Diantha B Howard; Indra Neil Sarkar
Journal:  AMIA Annu Symp Proc       Date:  2015-11-05

Review 8.  Methodological challenges and analytic opportunities for modeling and interpreting Big Healthcare Data.

Authors:  Ivo D Dinov
Journal:  Gigascience       Date:  2016-02-25       Impact factor: 6.524

9.  Natural language processing and recurrent network models for identifying genomic mutation-associated cancer treatment change from patient progress notes.

Authors:  Meijian Guan; Samuel Cho; Robin Petro; Wei Zhang; Boris Pasche; Umit Topaloglu
Journal:  JAMIA Open       Date:  2019-01-03

10.  Mapping Multi-Site Clinic Workflows to Design Systems-Enabled Interventions.

Authors:  Gloria D Coronado; Sally Retecki; Amanda F Petrik; Jennifer Coury; Josue Aguirre; Stephen H Taplin; Tim Burdick; Beverly B Green
Journal:  EGEMS (Wash DC)       Date:  2017-06-14
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