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Combining Structured and Free-text Electronic Medical Record Data for Real-time Clinical Decision Support

Emilia Apostolova, Tony Wang, Tim Tschampel, Ioannis Koutroulis, Tom Velez
2019 Proceedings of the 18th BioNLP Workshop and Shared Task  
The goal of this work is to utilize Electronic Medical Record (EMR) data for real-time Clinical Decision Support (CDS).  ...  We present a deep learning approach to combining in real time available diagnosis codes (ICD codes) and free-text notes: Patient Context Vectors.  ...  Acknowledgements Research reported in this publication was supported by a NIH SBIR award to CTA by NIH National Heart, Lung, and Blood Institute, of the National Institutes of Health under award number  ... 
doi:10.18653/v1/w19-5007 dblp:conf/bionlp/ApostolovaWTKV19 fatcat:ylphmzzhajffljd2w72wpctydu

Electronic medical record phenotyping using the anchor and learn framework

Yoni Halpern, Steven Horng, Youngduck Choi, David Sontag
2016 JAMIA Journal of the American Medical Informatics Association  
Materials and Methods We developed a phenotype library that uses both structured and unstructured data from the EMR to represent patients for real-time clinical decision support.  ...  As medicine becomes increasingly precise, a patient's electronic medical record phenotype will play an important role in triggering clinical decision support systems that can deliver personalized recommendations  ...  phenotypes for activating clinical decision support in real time.  ... 
doi:10.1093/jamia/ocw011 pmid:27107443 pmcid:PMC4926745 fatcat:4gkacr44zjgori6zgq7pcb6pq4

In response to: Method of electronic health record documentation and quality of primary care

Jonathan A Handler, James G Adams
2012 JAMIA Journal of the American Medical Informatics Association  
However, they also write, 'Until large scale NLP can produce structured data from dictated and free text reports, structured data entry will be an essential input to both clinical decision support and  ...  clinical decision support.'  ... 
doi:10.1136/amiajnl-2012-001149 pmid:22842547 pmcid:PMC3534472 fatcat:mi2kvnihyvfirauv7zersygfse

The freetext matching algorithm: a computer program to extract diagnoses and causes of death from unstructured text in electronic health records

Anoop D Shah, Carlos Martinez, Harry Hemingway
2012 BMC Medical Informatics and Decision Making  
We present a platform that combines an approach to semantic extraction of medical information from clinical free-text documents with the processing of structured information from HIS records.  ...  The information extraction process uses a fine-grained linguistic analysis, and maps preprocessed terms to the concepts of domain-specific ontologies.  ...  Clinical trials make use of the information stored in electronic health records, but much of this information is encoded in free text rather than stored in structured records [5] . II.  ... 
doi:10.1186/1472-6947-12-88 pmid:22870911 pmcid:PMC3483188 fatcat:qvffnbot5jdormq6dgoyephymq

Current Development and Technology in the Information Extraction for Clinical Narrative Text

Yan Ge
2015 International Journal of Computer Science and Application  
We mainly introduce the Hidden Markov Model, Support Vector Machine, Ontology and other combined method used in information extraction for clinical narratives.  ...  Most of the clinical narratives are free-text forms.  ...  Bansal for his valuable discussions and support.  ... 
doi:10.12783/ijcsa.2015.0402.01 fatcat:4cch3i72jjbo5hvnbbssvwnnpi

From Learning About Machines to Machine Learning: Applications for Mental Health Rehabilitation

Jaya Chaturvedi
2020 Journal of Psychosocial Rehabilitation and Mental Health  
Clinical decision support systems can assist in this development of personalised rehabilitation measures by simulating human decision making and combining this with understanding the underlying data of  ...  The SLaM Biomedical Research Centre Case Register and its Clinical Record Interactive Search (CRIS) application were developed in 2008, generating a research repository of real-time, anonymised, structured  ... 
doi:10.1007/s40737-020-00163-y fatcat:iwnteso5e5bp3a5d3l4umxvwce

Towards a symbiotic relationship between big data, artificial intelligence, and hospital pharmacy

Carlos Del Rio-Bermudez, Ignacio H. Medrano, Laura Yebes, Jose Luis Poveda
2020 Journal of Pharmaceutical Policy and Practice  
The digitalization of health and medicine and the growing availability of electronic health records (EHRs) has encouraged healthcare professionals and clinical researchers to adopt cutting-edge methodologies  ...  to improve patient care and perform real-time evaluations of the efficacy, safety, and comparative effectiveness of available drugs.  ...  , and shows great promise for the generation of computerized clinical decision support (CDS) [16] .  ... 
doi:10.1186/s40545-020-00276-6 pmid:33292570 fatcat:up5sgx6idrfb3ce5qwmzew4xrq

Informatics Infrastructure for Syndrome Surveillance, Decision Support, Reporting, and Modeling of Critical Illness

Vitaly Herasevich, Brian W. Pickering, Yue Dong, Steve G. Peters, Ognjen Gajic
2010 Mayo Clinic proceedings  
METHODS: Using open-schema data feeds imported from electronic medical records (EMRs), we developed a near-real-time relational database (Multidisciplinary Epidemiology and Translational Research in Intensive  ...  Open database connectivity supported the use of Boolean combinations of data that allowed authorized users to develop syndrome surveillance, decision support, and reporting (data "sniffers") routines.  ...  We have deployed computerized clincian order entry throughout Mayo Clinic hospitals and have introduced a number of decision support rules for real-time interventions.  ... 
doi:10.4065/mcp.2009.0479 pmid:20194152 pmcid:PMC2843116 fatcat:66tmrrsdkfb4lgnglchvdpsnpy

An Efficient, Clinically-Natural Electronic Medical Record System that Produces Computable Data

Brent C. James, David P. Edwards, Alan F. James, Richard L. Bradshaw, Keith S. White, Chris Wood, Stan Huff
2017 eGEMs  
Current commercially-available electronic medical record systems produce mainly text-based information focused on financial and regulatory performance.  ...  The clinical decision support approach increased the structure of textual clinical documentation, to the point where established methods for converting text into computable data (natural language processing  ...  Clinicians may need to supplement an activity's structured data with free text notes. The ART supports direct typing or voice recognition for that purpose.  ... 
doi:10.5334/egems.202 pmid:29881757 pmcid:PMC5982922 fatcat:uxge6jixzzctjannneaaxngw7u

From Free-Text to Structure in Electronic Patient Records

Gro-Hilde Severinsen, Line Silsand, Gunnar Ellingsen, Rune Pedersen
2019 Studies in Health Technology and Informatics  
to a structured EPR system constituting important preconditions for establishing advanced decision support and reuse of healthcare data.  ...  How will the need for semantic interoperability between different EPRs influence the goal of advanced clinical decision support?  ...  . / From Free-Text to Structure in Electronic Patient Records G.-H. Severinsen et al. / From Free-Text to Structure in Electronic Patient Records  ... 
doi:10.3233/shti190143 pmid:31431582 fatcat:h623iho2u5gyvc6qxxrciruaie

Data Gaps in Electronic Health Record (EHR) Systems: An Audit of Problem List Completeness During the COVID-19 Pandemic

Jordan Poulos, Leilei Zhu, Anoop D. Shah
2021 International Journal of Medical Informatics  
Diagnoses and other clinical information stored in a structured way in electronic health records is extremely useful for supporting clinical decisions, improving patient care and enabling better research  ...  However, recording of medical diagnoses on the structured problem list for inpatients is incomplete, with almost 40% of important diagnoses mentioned only in the free text notes.  ...  topic • Diagnoses and other clinical information stored in a structured way in electronic health records is extremely useful for supporting clinical decisions, improving patient care and enabling better  ... 
doi:10.1016/j.ijmedinf.2021.104452 pmid:33864979 fatcat:dc3f5bzx2jd2rn2kawytifmmwu

The Emerging Role of Electronic Medical Records in Pharmacogenomics

R A Wilke, H Xu, J C Denny, D M Roden, R M Krauss, C A McCarty, R L Davis, T Skaar, J Lamba, G Savova
2011 Clinical Pharmacology and Therapeutics  
providing real-time decision support.  ...  9,10 health-care information technology and genotyping technology are both advancing rapidly, creating new opportunities for medical and scientific discovery.  ...  Electronic medical records (EMRs) typically contain a combination of unstructured text reports and structured data.  ... 
doi:10.1038/clpt.2010.260 pmid:21248726 pmcid:PMC3204342 fatcat:wwchsgqmpzas5iaeeszdkx6x7q

Automated Outcome Classification of Emergency Department Computed Tomography Imaging Reports

Kabir Yadav, Efsun Sarioglu, Meaghan Smith, Hyeong-Ah Choi, Craig D. Newgard
2013 Academic Emergency Medicine  
Background-Reliably abstracting outcomes from free-text electronic medical records remains a challenge.  ...  While automated classification of free text has been a popular medical informatics topic, performance validation using real-world clinical data has been limited.  ...  Medical Language Extraction and Encoding (MedLEE) was developed with support from the National Library of Medicine (R01LM010016 and R01LM008635).  ... 
doi:10.1111/acem.12174 pmid:24033628 pmcid:PMC3898888 fatcat:v2fxoa6s3jbvhihli23oytnxge

A Medical Decision Support System for the Differential Diagnosis Based on Medical Information Text Mining

Andreas Kanavos
2020 Biomedical Journal of Scientific & Technical Research  
Many Information and Communication Technologies (ICT) tools promise to help and support a medical decision in diagnosing diseases.  ...  More to the point, doctors' logic concerns data retrieval from knowledge recorded in their memory, combining thus more descriptive expressions that describe symptoms critical for concluding the correct  ...  support the medical decision and take place in real-time, facilitating the work of doctors.  ... 
doi:10.26717/bjstr.2020.30.005020 fatcat:53kylkomynfxlpxrqcfsf6kyky

Key Contributions in Clinical Research Informatics

Christel Daniel, Ali Bellamine, Dipak Kalra, Section Editors of the IMIA Yearbook Section on Clinical Research Informatics
2021 IMIA Yearbook of Medical Informatics  
Method: A bibliographic search using a combination of Medical Subject Headings (MeSH) descriptors and free-text terms on CRI was performed using PubMed, followed by a double-blind review in order to select  ...  (AI/ML) algorithms based on ever more intensive use of real-world data and especially EHR real or synthetic data.  ...  for their contribution to the selection process of the Clinical Research Informatics section for the IMIA Yearbook 2021.  ... 
doi:10.1055/s-0041-1726514 pmid:34479395 fatcat:zaop3wfv5fhplnompbmyxc6rzi
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