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Unified Medical Language System

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1. Knowledge Discovery from Posts in Online Health Communities Using Unified Medical Language System (PubMed)

Knowledge Discovery from Posts in Online Health Communities Using Unified Medical Language System Patient-reported posts in Online Health Communities (OHCs) contain various valuable information that can help establish knowledge-based online support for online patients. However, utilizing these reports to improve online patient services in the absence of appropriate medical and healthcare expert knowledge is difficult. Thus, we propose a comprehensive knowledge discovery method that is based (...) on the Unified Medical Language System for the analysis of narrative posts in OHCs. First, we propose a domain-knowledge support framework for OHCs to provide a basis for post analysis. Second, we develop a Knowledge-Involved Topic Modeling (KI-TM) method to extract and expand explicit knowledge within the text. We propose four metrics, namely, explicit knowledge rate, latent knowledge rate, knowledge correlation rate, and perplexity, for the evaluation of the KI-TM method. Our experimental results indicate

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2018 International journal of environmental research and public health

2. ODMSummary: A Tool for Automatic Structured Comparison of Multiple Medical Forms Based on Semantic Annotation with the Unified Medical Language System. (PubMed)

ODMSummary: A Tool for Automatic Structured Comparison of Multiple Medical Forms Based on Semantic Annotation with the Unified Medical Language System. Medical documentation is applied in various settings including patient care and clinical research. Since procedures of medical documentation are heterogeneous and developed further, secondary use of medical data is complicated. Development of medical forms, merging of data from different sources and meta-analyses of different data sets (...) of forms, enable to estimate the documentation effort, track changes in different versions of forms and find comparable items in different forms. Forms are provided in Operational Data Model format with semantic annotations from the Unified Medical Language System. 12 medical experts were invited to participate in a 3-phase evaluation of the tool regarding usability.ODMSummary (available at https://odmtoolbox.uni-muenster.de/summary/summary.html) provides a structured overview of multiple forms

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2016 PLoS ONE

3. Integrating unified medical language system and association mining techniques into relevance feedback for biomedical literature search (PubMed)

Integrating unified medical language system and association mining techniques into relevance feedback for biomedical literature search Finding highly relevant articles from biomedical databases is challenging not only because it is often difficult to accurately express a user's underlying intention through keywords but also because a keyword-based query normally returns a long list of hits with many citations being unwanted by the user. This paper proposes a novel biomedical literature search (...) . BiomedSearch relies on Unified Medical Language System (UMLS) knowledge sources to map text files to standard biomedical concepts. It was designed to support queries with any levels of complexity.A prototype of BiomedSearch software was made and it was preliminarily evaluated using the Genomics data from TREC (Text Retrieval Conference) 2006 Genomics Track. Initial experiment results indicated that BiomedSearch increased the mean average precision (MAP) for a set of queries.With UMLS and association mining

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2016 BMC bioinformatics

4. Unified Medical Language System

Unified Medical Language System Unified Medical Language System Toggle navigation Brain Head & Neck Chest Endocrine Abdomen Musculoskeletal Skin Infectious Disease Hematology & Oncology Cohorts Diagnostics Emergency Findings Procedures Prevention & Management Pharmacy Resuscitation Trauma Emergency Procedures Ultrasound Cardiovascular Emergencies Lung Emergencies Infectious Disease Pediatrics Neurologic Emergencies Skin Exposure Miscellaneous Abuse Cancer Administration 4 Unified Medical (...) Language System Unified Medical Language System Aka: Unified Medical Language System , UMLS From Related Chapters II. Background History Started in 1986 at the National Library of Medicine Description Library of mappings of clinical terms and codes to various clinical vocabularies, as well as their organization within a hierarchical tree Free for use within the U.S. Features Concept Unique Identifiers (CUI) codes are assigned to each unique concept Concept codes only exist if they are present in one

2018 FP Notebook

5. Longitudinal analysis of pain in patients with metastatic prostate cancer using natural language processing of medical record text. (PubMed)

prostate cancer (Project to ELIminate lethal CANcer) was subjected to natural language processing (NLP) using Unified Medical Language System-based terms. A four-tiered pain scale was developed, and logistic regression analysis identified factors that correlated with experience of severe pain during each month.NLP identified 6387 pain and 13 827 drug mentions in the text. Graphical displays revealed the pain 'landscape' described in the textual records and confirmed dramatically increasing levels (...) Longitudinal analysis of pain in patients with metastatic prostate cancer using natural language processing of medical record text. To test the feasibility of using text mining to depict meaningfully the experience of pain in patients with metastatic prostate cancer, to identify novel pain phenotypes, and to propose methods for longitudinal visualization of pain status.Text from 4409 clinical encounters for 33 men enrolled in a 15-year longitudinal clinical/molecular autopsy study of metastatic

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2017 Journal of the American Medical Informatics Association

6. Medical subdomain classification of clinical notes using a machine learning-based natural language processing approach. (PubMed)

of the note.We constructed the pipeline using the clinical NLP system, clinical Text Analysis and Knowledge Extraction System (cTAKES), the Unified Medical Language System (UMLS) Metathesaurus, Semantic Network, and learning algorithms to extract features from two datasets - clinical notes from Integrating Data for Analysis, Anonymization, and Sharing (iDASH) data repository (n = 431) and Massachusetts General Hospital (MGH) (n = 91,237), and built medical subdomain classifiers with different combinations (...) Medical subdomain classification of clinical notes using a machine learning-based natural language processing approach. The medical subdomain of a clinical note, such as cardiology or neurology, is useful content-derived metadata for developing machine learning downstream applications. To classify the medical subdomain of a note accurately, we have constructed a machine learning-based natural language processing (NLP) pipeline and developed medical subdomain classifiers based on the content

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2017 Medical Informatics and Decision Making

7. A chemical specialty semantic network for the Unified Medical Language System (PubMed)

A chemical specialty semantic network for the Unified Medical Language System Terms representing chemical concepts found the Unified Medical Language System (UMLS) are used to derive an expanded semantic network with mutually exclusive semantic types. The UMLS Semantic Network (SN) is composed of a collection of broad categories called semantic types (STs) that are assigned to concepts. Within the UMLS's coverage of the chemical domain, we find a great deal of concepts being assigned more than

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2012 Journal of Cheminformatics

8. Unified Medical Language System

Unified Medical Language System Unified Medical Language System Toggle navigation Brain Head & Neck Chest Endocrine Abdomen Musculoskeletal Skin Infectious Disease Hematology & Oncology Cohorts Diagnostics Emergency Findings Procedures Prevention & Management Pharmacy Resuscitation Trauma Emergency Procedures Ultrasound Cardiovascular Emergencies Lung Emergencies Infectious Disease Pediatrics Neurologic Emergencies Skin Exposure Miscellaneous Abuse Cancer Administration 4 Unified Medical (...) Language System Unified Medical Language System Aka: Unified Medical Language System , UMLS From Related Chapters II. Background History Started in 1986 at the National Library of Medicine Description Library of mappings of clinical terms and codes to various clinical vocabularies, as well as their organization within a hierarchical tree Free for use within the U.S. Features Concept Unique Identifiers (CUI) codes are assigned to each unique concept Concept codes only exist if they are present in one

2015 FP Notebook

9. Performance evaluation of Unified Medical Language System(R)'s synonyms expansion to query PubMed. (PubMed)

Performance evaluation of Unified Medical Language System(R)'s synonyms expansion to query PubMed. PubMed is the main access to medical literature on the Internet. In order to enhance the performance of its information retrieval tools, primarily non-indexed citations, the authors propose a method: expanding users' queries using Unified Medical Language System' (UMLS) synonyms i.e. all the terms gathered under one unique Concept Unique Identifier.This method was evaluated using queries

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2012 Medical Informatics and Decision Making

10. Responsible use of high-risk medical devices: the example of 3D printed medical devices

contributions were inclusive in the respective parts of the report. However, there is no separate section on overall ethical aspects. Text box 1 – High-risk medical devices Medical devices are segmented into classes according to the risk associated. To determine classification, a set of criteria can be combined in various ways in order to determine classification, e.g. duration of contact with the body, degree of invasiveness and local vs. systemic effect. The criteria and rules for classification (...) of medical devices are set out in annex 9 of the European Directive 93/42/EEC. Class IIb (medium/high-risk) and Class III (high-risk) include high-risk medical devices. It concerns amongst others implantable devices and long-term surgically invasive devices such as hip-, breast-, knee implants and implantable devices and surgically invasive devices that come in contact with the heart, the central nervous system or the central circulatory system or intended to control, diagnose, monitor or correct

2018 Belgian Health Care Knowledge Centre

11. Handbook on designing and implementing an immunisation information system

of ICTs in health products, services and processes combined with organisational change in healthcare systems and new skills, in order to improve health of citizens, efficiency and productivity in healthcare delivery, and the economic and social value of health [1] mHealth European Commission definition: mobile health is a sub-segment of eHealth and covers medical and public health practice supported by mobile devices. It especially includes the use of mobile communication devices for health and well (...) of the immunisation programmes in some countries, including general practitioners (GPs), paediatricians, nurses, gynaecologists and school nurses. There has been a corresponding increase in need for specialist advice on vaccine indications and contra-indications, and this can be offered by IIS through clinical decision support systems and through the medical information that can be provided. IIS can provide access to consolidated immunisation data at the time and place where a decision on vaccination

2019 European Centre for Disease Prevention and Control - Technical Guidance

12. Preparing Emerging Leaders for Alternative Futures in Health Systems Across Canada

capacity in Canada. These include: 1) the broad acceptance of the LEADS in a Caring Environment Framework in providing a common language and guide to understanding Preparing Emerging Leaders for Alternative Futures in Health Systems Across Canada 10 Evidence >> Insight >> Action leadership (particularly in provinces outside of Ontario); 2) the development of additional leadership-focused efforts internationally, such as the American College of Healthcare Executives (ACHE) competencies framework (...) determinants of health o Increase in medical tourism with affluent consumers seeking care overseas • Political o Governments focus their efforts of regulating large integrated-care providers and funding services for those unable to purchase care o Limited success in making health-system transformations leads to apathy and disillusionment with government • Environmental o Climate change leads to bacteria, some of which are antibiotic resistant, and other causes of disease • Technological o Organizations

2019 McMaster Health Forum

13. Applying natural language processing techniques to develop a task-specific EMR interface for timely stroke thrombolysis: A feasibility study. (PubMed)

and expanded the concepts using the Unified Medical Language System Metathesaurus. Concepts identified from clinical notes by MetaMap were compared to those from IVT eligibility criteria. The task-specific EMR interface displays IVT-relevant information by highlighting phrases that contain matched concepts. Clinical usability was assessed with clinicians staffing the acute stroke team by comparing user performance while using the task-specific and the current EMR interfaces.The algorithm identified IVT (...) Applying natural language processing techniques to develop a task-specific EMR interface for timely stroke thrombolysis: A feasibility study. To reduce errors in determining eligibility for intravenous thrombolytic therapy (IVT) in stroke patients through use of an enhanced task-specific electronic medical record (EMR) interface powered by natural language processing (NLP) techniques.The information processing algorithm utilized MetaMap to extract medical concepts from IVT eligibility criteria

2018 International journal of medical informatics

14. Unique Clinical Language Patterns Among Expert Vestibular Providers Can Predict Vestibular Diagnoses. (PubMed)

Bayes predictive models correlating language usage with clinical diagnoses.Natural language analyses on 866 physician-generated histories from vestibular patients found 3,286 unique examples of language usage of which 614 were used 10 or greater times. The top 15 semantic types represented only 11% of all Unified Medical Language System semantic types but covered 86% of language used in vestibular patient histories. Naïve Bayes machine learning algorithms on a subset of 255 notes representing benign (...) conserved. These patterns have strong predictive power toward specific vestibular diagnoses. Such language elements can provide a simple vocabulary to aid nonexpert providers in formulating a differential diagnosis. They can also be incorporated into clinical decision support systems to facilitate accurate vestibular diagnosis in ambulatory settings.

2018 Otology and Neurotology

15. Evaluating the impact of pre-annotation on annotation speed and potential bias: natural language processing gold standard development for clinical named entity recognition in clinical trial announcements. (PubMed)

the clinicaltrials.gov website were randomly selected and double annotated for diagnoses, signs, symptoms, Unified Medical Language System (UMLS) Concept Unique Identifiers, and SNOMED CT codes. We used two dictionary-based methods to pre-annotate the text. We evaluated the annotation time and potential bias through F-measures and ANOVA tests and implemented Bonferroni correction.Time savings ranged from 13.85% to 21.5% per entity. Inter-annotator agreement (IAA) ranged from 93.4% to 95.5 (...) Evaluating the impact of pre-annotation on annotation speed and potential bias: natural language processing gold standard development for clinical named entity recognition in clinical trial announcements. To present a series of experiments: (1) to evaluate the impact of pre-annotation on the speed of manual annotation of clinical trial announcements; and (2) to test for potential bias, if pre-annotation is utilized.To build the gold standard, 1400 clinical trial announcements from

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2017 Journal of the American Medical Informatics Association

16. Shared Medical Appointments for Chronic Medical Conditions: A Systematic Review

Shared Medical Appointments for Chronic Medical Conditions: A Systematic Review Evidence-based Synthesis Program Department of Veterans Affairs Health Services Research & Development Service July 2012 Prepared for: Department of Veterans Affairs Veterans Health Administration Quality Enhancement Research Initiative Health Services Research & Development Service Washington, DC 20420 Prepared by: Evidence-based Synthesis Program (ESP) Center Durham Veterans Affairs Healthcare System Durham, NC (...) criteria 12 Table 2. Overview of studies evaluating SMA 17 Table 3. Characteristics of shared medical appointment interventions 18 Table 4. Study details for SMAs enrolling adults with diabetes 20 Table 5. Summary of the intervention effects and SOE for KQ 1 28 Table 6. Implementation issues 31 Table 7. Evidence gaps and future research 321 Shared Medical Appointments for Chronic Medical Conditions Evidence-based Synthesis Program EXECUTIVE SUMMARY BACKGROUND The most successful health care systems

2012 Veterans Affairs Evidence-based Synthesis Program Reports

17. The Learning Healthcare System and Cardiovascular Care: A Scientific Statement From the American Heart Association

, comorbidities, medications, test results, and preferences. Furthermore, once these decisions are made, little information is available about their impact, limiting the ability to learn from and ultimately improve care delivery. This inability of the healthcare system to learn from its operation results in significant inefficiencies, substantial costs, and suboptimal health outcomes. The creation of a learning healthcare system (LHS) can potentially address these issues. The LHS uses health information (...) systems—hospitals, medical groups, accountable care organizations—where CVD care occurs. We also hope this road map for realizing the LHS concepts in CVD care will inform similar efforts in the broader healthcare system. LHS Science and Informatics In response to the informational imperative, the ideal LHS collects, organizes, and analyzes the massive amount of clinical information available to providers and patients to provide tailored insights into optimal care decisions and delivery

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2017 American Heart Association

18. Building a Natural Language Processing Tool to Identify Patients with High Clinical Suspicion for Kawasaki Disease from Emergency Department Notes. (PubMed)

diagnostic criteria based on standard clinical terms and medical word usage using 22 pediatric ED notes augmented by Unified Medical Language System vocabulary. With high suspicion for KD defined as fever and three or more KD clinical signs, KD-NLP was applied to 253 ED notes from children ultimately diagnosed with either KD or another febrile illness. We evaluated KD-NLP performance against ED notes manually reviewed by clinicians and compared the results to a simple keyword search.KD-NLP identified (...) Building a Natural Language Processing Tool to Identify Patients with High Clinical Suspicion for Kawasaki Disease from Emergency Department Notes. Delayed diagnosis of Kawasaki disease (KD) may lead to serious cardiac complications. We sought to create and test the performance of a natural language processing (NLP) tool, the KD-NLP, in the identification of emergency department (ED) patients for whom the diagnosis of KD should be considered.We developed an NLP tool that recognizes the KD

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2016 Academic Emergency Medicine

19. Web-Based Information Infrastructure Increases the Interrater Reliability of Medical Coders: Quasi-Experimental Study. (PubMed)

Web-Based Information Infrastructure Increases the Interrater Reliability of Medical Coders: Quasi-Experimental Study. Medical coding is essential for standardized communication and integration of clinical data. The Unified Medical Language System by the National Library of Medicine is the largest clinical terminology system for medical coders and Natural Language Processing tools. However, the abundance of ambiguous codes leads to low rates of uniform coding among different coders.The (...) objective of our study was to measure uniform coding among different medical experts in terms of interrater reliability and analyze the effect on interrater reliability using an expert- and Web-based code suggestion system.We conducted a quasi-experimental study in which 6 medical experts coded 602 medical items from structured quality assurance forms or free-text eligibility criteria of 20 different clinical trials. The medical item content was selected on the basis of mortality-leading diseases

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2018 Journal of medical Internet research

20. Using data-driven sublanguage pattern mining to induce knowledge models: application in medical image reports knowledge representation. (PubMed)

-of-speech parser and the "Subject:Relationship:Object" syntactic data schema. The identified noun phrases were tagged with the Unified Medical Language System (UMLS) semantic types. An evaluation was done on a dataset comprised of 83 image notes from four data sources.A semantic type network was built based on the co-occurrence of 135 UMLS semantic types in 23,410 medical image reports. By regrouping the semantic types and generalizing the semantic network, we created a knowledge model that contains 14 (...) and relationships. In this paper, we described a data-driven sublanguage pattern mining method that can be used to create a knowledge model. We combined natural language processing (NLP) and semantic network analysis in our model generation pipeline.As a use case of our pipeline, we utilized data from an open source imaging case repository, Radiopaedia.org , to generate a knowledge model that represents the contents of medical imaging reports. We extracted entities and relationships using the Stanford part

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2018 Medical Informatics and Decision Making

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