Literature DB >> 28130331

MetaMap Lite: an evaluation of a new Java implementation of MetaMap.

Dina Demner-Fushman1, Willie J Rogers1, Alan R Aronson1.   

Abstract

MetaMap is a widely used named entity recognition tool that identifies concepts from the Unified Medical Language System Metathesaurus in text. This study presents MetaMap Lite, an implementation of some of the basic MetaMap functions in Java. On several collections of biomedical literature and clinical text, MetaMap Lite demonstrated real-time speed and precision, recall, and F1 scores comparable to or exceeding those of MetaMap and other popular biomedical text processing tools, clinical Text Analysis and Knowledge Extraction System (cTAKES) and DNorm. Published by Oxford University Press on behalf of the American Medical Informatics Association 2017. This work is written by US Government employees and is in the public domain in the US.

Keywords:  algorithms; natural language processing; software design; software validation; unified medical language system

Mesh:

Year:  2017        PMID: 28130331      PMCID: PMC6080672          DOI: 10.1093/jamia/ocw177

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  16 in total

1.  Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications.

Authors:  Guergana K Savova; James J Masanz; Philip V Ogren; Jiaping Zheng; Sunghwan Sohn; Karin C Kipper-Schuler; Christopher G Chute
Journal:  J Am Med Inform Assoc       Date:  2010 Sep-Oct       Impact factor: 4.497

2.  The Yale cTAKES extensions for document classification: architecture and application.

Authors:  Vijay Garla; Vincent Lo Re; Zachariah Dorey-Stein; Farah Kidwai; Matthew Scotch; Julie Womack; Amy Justice; Cynthia Brandt
Journal:  J Am Med Inform Assoc       Date:  2011-05-27       Impact factor: 4.497

3.  Challenges in clinical natural language processing for automated disorder normalization.

Authors:  Robert Leaman; Ritu Khare; Zhiyong Lu
Journal:  J Biomed Inform       Date:  2015-07-14       Impact factor: 6.317

4.  NCBI disease corpus: a resource for disease name recognition and concept normalization.

Authors:  Rezarta Islamaj Doğan; Robert Leaman; Zhiyong Lu
Journal:  J Biomed Inform       Date:  2014-01-03       Impact factor: 6.317

5.  ConText: an algorithm for determining negation, experiencer, and temporal status from clinical reports.

Authors:  Henk Harkema; John N Dowling; Tyler Thornblade; Wendy W Chapman
Journal:  J Biomed Inform       Date:  2009-05-10       Impact factor: 6.317

6.  MEDIC: a practical disease vocabulary used at the Comparative Toxicogenomics Database.

Authors:  Allan Peter Davis; Thomas C Wiegers; Michael C Rosenstein; Carolyn J Mattingly
Journal:  Database (Oxford)       Date:  2012-03-20       Impact factor: 3.451

7.  CD-REST: a system for extracting chemical-induced disease relation in literature.

Authors:  Jun Xu; Yonghui Wu; Yaoyun Zhang; Jingqi Wang; Hee-Jin Lee; Hua Xu
Journal:  Database (Oxford)       Date:  2016-03-25       Impact factor: 3.451

8.  The BioScope corpus: biomedical texts annotated for uncertainty, negation and their scopes.

Authors:  Veronika Vincze; György Szarvas; Richárd Farkas; György Móra; János Csirik
Journal:  BMC Bioinformatics       Date:  2008-11-19       Impact factor: 3.169

9.  DNorm: disease name normalization with pairwise learning to rank.

Authors:  Robert Leaman; Rezarta Islamaj Dogan; Zhiyong Lu
Journal:  Bioinformatics       Date:  2013-08-21       Impact factor: 6.937

10.  NOBLE - Flexible concept recognition for large-scale biomedical natural language processing.

Authors:  Eugene Tseytlin; Kevin Mitchell; Elizabeth Legowski; Julia Corrigan; Girish Chavan; Rebecca S Jacobson
Journal:  BMC Bioinformatics       Date:  2016-01-14       Impact factor: 3.169

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  40 in total

1.  Deep Learning Meets Biomedical Ontologies: Knowledge Embeddings for Epilepsy.

Authors:  Ramon Maldonado; Travis R Goodwin; Michael A Skinner; Sanda M Harabagiu
Journal:  AMIA Annu Symp Proc       Date:  2018-04-16

2.  Prediction of breast cancer distant recurrence using natural language processing and knowledge-guided convolutional neural network.

Authors:  Hanyin Wang; Yikuan Li; Seema A Khan; Yuan Luo
Journal:  Artif Intell Med       Date:  2020-11-01       Impact factor: 5.326

3.  Consumer health information and question answering: helping consumers find answers to their health-related information needs.

Authors:  Dina Demner-Fushman; Yassine Mrabet; Asma Ben Abacha
Journal:  J Am Med Inform Assoc       Date:  2020-02-01       Impact factor: 4.497

4.  Deep Learning from Incomplete Data: Detecting Imminent Risk of Hospital-acquired Pneumonia in ICU Patients.

Authors:  Travis R Goodwin; Dina Demner-Fushman
Journal:  AMIA Annu Symp Proc       Date:  2020-03-04

5.  Comparative Analysis of Patient Distress in Opioid Treatment Programs using Natural Language Processing.

Authors:  Fatemeh Shah-Mohammadi; Wanting Cui; Keren Bachi; Yasmin Hurd; Joseph Finkelstein
Journal:  Biomed Eng Syst Technol Int Jt Conf BIOSTEC Revis Sel Pap       Date:  2022-02

6.  A Comparison of Natural Language Processing Methods for the Classification of Lumbar Spine Imaging Findings Related to Lower Back Pain.

Authors:  Chethan Jujjavarapu; Vikas Pejaver; Trevor A Cohen; Sean D Mooney; Patrick J Heagerty; Jeffrey G Jarvik
Journal:  Acad Radiol       Date:  2021-12-01       Impact factor: 3.173

7.  Controversial Trials First: Identifying Disagreement Between Clinical Guidelines and New Evidence.

Authors:  Florian Borchert; Laura Meister; Thomas Langer; Markus Follmann; Bert Arnrich; Matthieu-P Schapranow
Journal:  AMIA Annu Symp Proc       Date:  2022-02-21

8.  A customizable deep learning model for nosocomial risk prediction from critical care notes with indirect supervision.

Authors:  Travis R Goodwin; Dina Demner-Fushman
Journal:  J Am Med Inform Assoc       Date:  2020-04-01       Impact factor: 4.497

9.  Ensembles of natural language processing systems for portable phenotyping solutions.

Authors:  Cong Liu; Casey N Ta; James R Rogers; Ziran Li; Junghwan Lee; Alex M Butler; Ning Shang; Fabricio Sampaio Peres Kury; Liwei Wang; Feichen Shen; Hongfang Liu; Lyudmila Ena; Carol Friedman; Chunhua Weng
Journal:  J Biomed Inform       Date:  2019-10-23       Impact factor: 6.317

10.  Using computable knowledge mined from the literature to elucidate confounders for EHR-based pharmacovigilance.

Authors:  Scott A Malec; Peng Wei; Elmer V Bernstam; Richard D Boyce; Trevor Cohen
Journal:  J Biomed Inform       Date:  2021-03-11       Impact factor: 6.317

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