Apache cTAKES 2015


Resources:

  • ctakes .. system for extraction of information from electronic medical record clinical free-text
  • negex .. java classes for negation detection in clinical notes
  • ohnlp .. open health natural language processing consortium

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Apache cTAKES 2014


Information extraction from clinical documents: Towards disease/disorder template filling VR Chikka, N Mariyasagayam, Y Niwa… – … Conference of the Cross …, 2015 – Springer … Keywords: NLP · Information extraction · Unified Medical Langu- gae System (UMLS) · Apache cTAKES · Relation extraction · Machine learning 1 Introduction … 393 Fig. 1. System Architecture and Processing Pipeline built upon Apache cTAKES. … Cited by 2 Related articles All 2 versions

Extraction of UMLS® Concepts Using Apache cTAKES™ for German Language. M Becker, B Böckmann – Studies in health technology and …, 2015 – europepmc.org Automatic information extraction of medical concepts and classification with semantic standards from medical reports is useful for standardization and for clinical research. This paper presents an approach for an UMLS concept extraction with a customized natural Related articles All 3 versions

Information Extraction from Clinical Documents: Towards Disease/Disorder Template Filling K Karlapalem – … , and Interaction: 6th International Conference of …, 2015 – books.google.com … Keywords: NLP· Information extraction· Unified Medical Langu- gae System (UMLS)· Apache cTAKES· Relation extraction· Machine learning 1 Introduction Electronic Health Records (EHRs) have known to be rich sources of patient information. … Related articles

PICO extraction by combining the robustness of machine-learning methods with the rule-based methods S Chabou, M Iglewski – Information Technology and Computer …, 2015 – ieeexplore.ieee.org … 2011, Vol. 4, 4. 13. CRF++: Yet Another CRF toolkit. CRF++: Yet Another CRF toolkit. [Online] 2013. http://crfpp.googlecode.com/svn/trunk/doc/index.html#templ 14. The Apache Software Foundation. Apache cTAKES. [Online] 2014. http://ctakes.apache.org/. Cited by 1 Related articles

Concept extraction from medical documents a contextual approach G Szenasi, C Lemnaru… – … and Processing (ICCP), …, 2015 – ieeexplore.ieee.org … In [3] the authors describe the Apache cTAKES – Apache clinical Text Analysis and Knowledge Extraction System. Document structuring and negation identification are discussed in the process of medical concept identification. … Related articles

Special issue on bio-ontologies and phenotypes LN Soldatova, N Collier… – Journal of …, 2015 – jbiomedsem.biomedcentral.com … combine the systems using a variety of learn-to-rank algorithms. The four systems are Apache cTAKES, the NCBO Annotator, BeCAS and MetaMap. The proposed ensemble approach leads to an improvement in harmonized mean … Related articles All 15 versions

Concept selection for phenotypes and diseases using learn to rank N Collier, A Oellrich, T Groza – Journal of …, 2015 – jbiomedsem.biomedcentral.com … We observed that whilst overall Apache cTAKES tended to outperform other stand-alone systems on a strong recall (R = 0.57), precision was low (P = 0.09) leading to low-to-moderate F1 measure (F1 = 0.16). … 0.0146. 0.0134. 0.0140. M3: Apache cTAKES. 0.0933. 0.5675. 0.1602. … Cited by 2 Related articles All 14 versions

Blulab: Temporal information extraction for the 2015 clinical tempeval challenge S Velupillai, DL Mowery, S Abdelrahman… – 2015 – diva-portal.org … for strict information extraction (F1: detection and accuracy: normaliza- tion) of TIMEXs (0.287 F1 and 0.354 accuracy), disease/disorder EVENTS (0.750 F1 and 0.589 ac- curacy), and EVENT attributes (0.676 F1 and 0.868 accuracy) leveraged the Apache cTAKES (Savova et al … Cited by 7 Related articles All 12 versions

Evaluating the state of the art in disorder recognition and normalization of the clinical narrative S Pradhan, N Elhadad, BR South… – Journal of the …, 2015 – jamia.oxfordjournals.org … It is highly configurable and uses a knowledge-intensive approach. cTAKES35—clinical Text Analysis and Knowledge Extraction System (cTAKES) is an open source Apache top-level project for information extraction from clinical narratives. … Cited by 39 Related articles All 13 versions

Structuring unstructured clinical narratives in OpenMRS with medical concept extraction RM Eshleman, H Yang, B Levine – … and Biomedicine (BIBM), …, 2015 – ieeexplore.ieee.org … Max Target Domain Recall cTAKES .89 .76 Clinical Narratives MetaMaJl .85 .78 Biomedical literature BANNER .85 .79 Biomedical literature MGrep .88 .68 Variable Apache cTAKES [5] implements an analytical pipeline ending with noun-phrase chunking and a dictionary … Cited by 1 Related articles All 8 versions

De-identification of Unstructured Clinical Data for Patient Privacy Protection SM Meystre – Medical Data Privacy Handbook, 2015 – Springer … These functionalities were adapted from OpenNLP [43], with trained models and the implementation of LVG found in Apache cTAKES [2]. The high sensitivity extraction component combines various methods to detect all possible PHI in clinical text. … Related articles All 3 versions

A preliminary study on automatic identification of patient smoking status in unstructured electronic health records J Jonnagaddala, HJ Dai, P Ray, ST Liaw – ACL-IJCNLP, 2015 – aclweb.org … We also would like to explore optimal topic size for smoking identification from relevant smoking related sentences and compare the performance of our system against various smoking identification systems available like Apache cTAKES (Savova et al., 2010). … Cited by 3 Related articles All 7 versions

Representing Clinical Diagnostic Criteria in Quality Data Model Using Natural Language Processing N Hong, D Li, Y Yu, H Liu, CG Chute, G Jiang – ACL-IJCNLP 2015, 2015 – aclweb.org … cTAKES is an open source Apache project and it is a NLP system for extraction of information from electronic medical record clinical free-text. … Apache UIMA and Mayo cTAKES UIMA and how it is used in the clinical domain.[cited May 10, 2015]: Available from: http://www. uio. … Related articles All 7 versions

A Lightweight Text Mining Tool for Multisite Research DJ Cronkite, DS Carrell – Journal of …, 2015 – digitalrepository.aurorahealthcare. … … We used the more comprehensive Apache Clinical Text Analysis and Knowledge Extraction System (cTAKES) as a comparison using the same dictionary and same notes. We stopped cTAKES after 8.5 days with 144701 (68.9%) complete. …

Diagnostic Knowledge Extraction from MedlinePlus: An Application for Infectious Diseases A Rodríguez-González, M Martínez-Romero… – … Conference on Practical …, 2015 – Springer … negatives. Another line would be to use a different NLP tool to process the input texts, for example Apache cTakes. Finally, we plan to extend our work to the domain of treatment information to enrich the knowledge extracted. … Cited by 3 Related articles All 3 versions

Sharing Models and Tools for Processing German Clinical Texts J Hellrich, F Matthies, E Faessler… – Studies in health …, 2015 – person.hst.aau.dk … clinical staff, hospitals, etc.). These 1 Corresponding Author. 2 http://ctakes.apache. org/ Digital Healthcare Empowering Europeans R. Cornet et al. (Eds.) © 2015 European Federation for Medical Informatics (EFMI). This article is … Cited by 1 Related articles All 5 versions

Fine-grained information extraction from German transthoracic echocardiography reports M Toepfer, H Corovic, G Fette… – BMC medical …, 2015 – bmcmedinformdecismak. … … systems for medical and in particular clinical information extraction have been introduced: MedLEE [3], MEDSYNDIKATE [4], HITEx (Health Information Text Extraction) [6], SeReMed [2], or Apache cTAKES (Clinical Text Analysis and Knowledge Extraction System) [5] – just to … Cited by 1 Related articles All 18 versions

[BOOK] Apache Solr D Shahi – 2015 – Springer Page 1. Shahi Apache Solr Apache Solr A Practical Approach to Enterprise Search — Dikshant Shahi THE EXPERT S VOICE® IN ENTERPRISE SEARCH Page 2. Apache Solr A Practical Approach to Enterprise Search Dikshant Shahi Page 3. … Cited by 1 All 4 versions

Combining Multiple Knowledge Sources: A Case Study of Drug Induced Liver Injury CL Overby, A Flores, G Palma, ME Vidal… – … Conference on Data …, 2015 – Springer … We will explore the use of existing programs to map biomedical text to concepts in a range of knowledge bases containing disease and phenotype information, including MetaMap [ 2 ], Apache cTAKES [ 24 ], and the NCBO annotator [ 14 ]. … Related articles All 4 versions

Social Media Mining with Natural Language Processing M Abdul-Mageed, M Dickinson – 2015 – scholarworks.iu.edu … Stanford tagger) Biomedical tagger: ? GENIA tagger: http://www.nactem.ac.uk/tsujii/ GENIA/tagger/ ? cTAKES (clinical Text Analysis and Knowledge Extraction System): https://ctakes.apache.org/index.html 14 / 46 Page 15. …

Extracting research-quality phenotypes from electronic health records to support precision medicine WQ Wei, JC Denny – Genome medicine, 2015 – genomemedicine.biomedcentral. … Skip to main content. Advertisement. Biomed Central logo Menu. Search Search. Publisher main menu. … Cited by 20 Related articles All 12 versions

A Combined Approach for Disease/Disorder Template Filling N Huynh, Q Ho – Knowledge and Systems Engineering (KSE), …, 2015 – ieeexplore.ieee.org … Optimizing Apache cTAKES for Disease/Disorder Template Filling:Team HITACHI in 2014 ShARe/CLEF eHealth Evaluation Lab. In Cappellato, L., Ferro, N., Halvey, M., Kraaij, W., eds.: Working Notes for CLEF 2014 Conference, Sheffeld, UK, 2014. Pages 111-123. … Cited by 1 Related articles

Semeval-2015 task 6: Clinical tempeval S Bethard, L Derczynski, G Savova, G Savova… – Proceedings of the 9th …, 2015 – aclweb.org … teams submitted a total of 13 runs: BluLab The team from Stockholm University and University of Utah participated in all tasks, us- ing supervised classifiers with features gen- erated by the Apache clinical Text Analysis and Knowledge Extraction System (cTAKES) 4. Their runs … Cited by 38 Related articles All 12 versions

Adapting existing natural language processing resources for cardiovascular risk factors identification in clinical notes A Khalifa, S Meystre – Journal of biomedical informatics, 2015 – Elsevier … For increased efficiency, the application main components were adapted from two existing NLP tools implemented in the Apache UIMA framework: Textractor (for dictionary-based lookup) and cTAKES (for preprocessing and smoking status detection). … Cited by 4 Related articles All 7 versions

A Systematic Review of Natural Language Processing in Healthcare OG Iroju, JO Olaleke – International Journal of Information …, 2015 – mecs-press.org … MedLEE has been shown to be accurate with a recall rate of 83% and 89% precision [21]. B. Clinical Text Analysis and Knowledge Extraction System (Ctakes) CTakes is an open source NLP engine under the Apache License. CTakes was developed in 2006 at the Mayo Clinic. … Related articles All 3 versions

An Introduction to Natural Language Processing: How You Can Get More From Those Electronic Notes You Are Generating AA Kimia, G Savova, A Landschaft… – Pediatric emergency …, 2015 – journals.lww.com Close Window. Close Window. Enter your Email address: Wolters Kluwer Health may email you for journal alerts and information, but is committed to maintaining your privacy and will not share your personal information without your express consent. … Cited by 4 Related articles All 4 versions

Comparison of Natural Language Processing Algorithms for Medical Texts MW Chen – 2015 – pdfs.semanticscholar.org … has received more traction in being used to understand clinical texts especially after its adoption as a top level project by the Apache Software Foundation. In 2013, cTAKES received the award for the highest number of citations that contributed to … Related articles All 3 versions

Semi-supervised Learning for Phenotyping Tasks D Dligach, T Miller, GK Savova – AMIA Annual Symposium …, 2015 – ncbi.nlm.nih.gov … We represent each chart as a set of UMLS concept unique identifiers (CUIs) which we extract from the patient’s records using Apache Clinical Text Analysis and Knowledge Extraction System (cTAKES; ctakes.apache.org) [13]. … Cited by 1 Related articles All 4 versions

Information Extraction from Medical Social Media K Denecke – Health Web Science, 2015 – Springer … anatomy and drugs. cTAKES was built using the Apache UIMA Unstructured Information Management Architecture engineering framework (see Sect. 7.2) and the OpenNLP natural language processing toolkit [92]. Its components … Related articles

Automated systems for the de-identification of longitudinal clinical narratives: Overview of 2014 i2b2/UTHealth shared task Track 1 A Stubbs, C Kotfila, Ö Uzuner – Journal of biomedical informatics, 2015 – Elsevier … The VHA’s BoB [19] is built on the Apache UIMA architecture [23] and uses cTAKES [24] to pre-process the documents. The system then uses a “stepwise hybrid” approach to removing PHI. In the first step, a “high sensitivity extraction … Cited by 10 Related articles All 5 versions

Generation of silver standard concept annotations from biomedical texts with special relevance to phenotypes A Oellrich, N Collier, D Smedley, T Groza – PloS one, 2015 – journals.plos.org … In this study, we leverage the annotations of four established concept recognition systems (the NCBO annotator, the clinical Text Analysis and Knowledge Extraction System (cTAKES – https://ctakes.apache.org/), the Biomedical Concept Annotation System (BeCAS) [16], and … Cited by 3 Related articles All 12 versions

Automatic concept recognition using the Human Phenotype Ontology reference and test suite corpora T Groza, S Köhler, S Doelken, N Collier… – …, 2015 – database.oxfordjournals.org … Other systems we might have applied include ConceptMapper (21), Whatizit (22), Bio/MedLee (23), Apache cTAKES (24), or the well-known MetaMap (25). These systems were, however, either difficult to access or did not provide … Cited by 12 Related articles All 7 versions

Semantic retrieval and navigation in clinical document collections M Kreuzthaler, P Daumke… – … —Health Informatics Meets …, 2015 – books.google.com … apache. org/solr/, lasst access: 30.01. 2015 [10] Apache UIMA, https://uima. apache. org/, last access: 30.01. 2015 [11] Savova, GK et al.(2010). Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications. … Cited by 3 Related articles All 4 versions

UIMA based solution in pharma text A Rao, T Joseph, VG Saipradeep… – … (BIBM), 2015 IEEE …, 2015 – ieeexplore.ieee.org … The Apache Unstructured Infonnation Management Applications (UIMA) framework consists of a set of modules that help in this [1]. UIMA pipelines released by the Open Health Natural Language Processing (OHNLP) consortium such as MedKATIP [2,3] and cTAKES [4] are … Related articles All 2 versions

Towards the Semantic Interpretation of Personal Health Messages from Social Media N Limsopatham, N Collier – Proceedings of the ACM First International …, 2015 – dl.acm.org … computational linguist. From these examples, we observe the use of non-standard language and abbreviation, such as gettin, 2nite, OMG and OCD. In addition, as shown 4http://metamap.nlm.nih.gov/ 5http://ctakes.apache.org/ … Cited by 2 Related articles All 3 versions

Identifying Medical Terms Related to Specific Diseases M Shekhar, VR Chikka, L Thomas… – … Conference on Data …, 2015 – ieeexplore.ieee.org … The authors of [16] provide the state of art system of i2b2 2010 shared/task where they used semi-supervised approaches through clustering and is trained using CRFs with rich set of features of text, UMLS, cTAKES [17] and MedLEE NLP system [18] for extracting medical terms. … Related articles All 5 versions

The digital revolution in phenotyping A Oellrich, N Collier, T Groza… – Briefings in …, 2015 – Oxford Univ Press … Although not specifically aimed at phenotypes, knowledge brokering tools such as MetaMap [34], the NCBO Annotator and the Apache cTAKES [54] have all been widely used for concept annotation of text to biomedical ontologies and could be used to yield these building … Cited by 7 Related articles All 4 versions

Prescription Extraction from Clinical Notes: Towards Automating EMR Medication Reconciliation Y Wang, SR Steinhubl, C Defilippi, K Ng… – AMIA Summits on …, 2015 – ncbi.nlm.nih.gov … have leveraged natural language processing (NLP) technologies to extract information embedded in clinical notes, including Medical Language Extraction and Encoding System (MedLEE)4: Apache clinical Text Analysis and Knowledge Extraction Systems (cTAKES)5; and … Related articles All 5 versions

Automated Extraction of Substance Use Information from Clinical Texts Y Wang, ES Chen, S Pakhomov… – AMIA Annual …, 2015 – ncbi.nlm.nih.gov … 2002:587–91. [PMC free article] [PubMed]. 21. cTAKES. Available from: http://ctakes.apache.org. 22. Albright D, Lanfranchi A, Fredriksen A, Styler WF, Warner C, Hwang JD, et al. Towards comprehensive syntactic and semantic annotations of the clinical narrative. … Cited by 2 Related articles All 4 versions

A context-aware approach for progression tracking of medical concepts in electronic medical records NW Chang, HJ Dai, J Jonnagaddala, CW Chen… – Journal of biomedical …, 2015 – Elsevier … Apache clinical Text Analysis and Knowledge Extraction System (cTAKES) v3.1.1 with UMLS 2014AA as the underlying dictionary was selected as the baseline system to recognize medications and the mention concepts. A … Cited by 5 Related articles All 5 versions

Drug Name Recognition: Approaches and Resources S Liu, B Tang, Q Chen, X Wang – Information, 2015 – mdpi.com … BioLemmatizer [28], Biomedical, http://biolemmatizer.sourceforge.net/. cTAKES [29], Clinical, http://ctakes.apache.org/. (2) Drug name recognition: This step recognizes drug names from unstructured texts and classifies them into predefined categories. … Cited by 4 Related articles All 3 versions

Reviewing 741 patients records in two hours with FASTVISU JB Escudié, AS Jannot, E Zapletal… – AMIA Annual …, 2015 – ncbi.nlm.nih.gov … to identify medical entities in free-text (popular MERs include MetaMap 18 developed by the National Library of Medicine, the Bioportal Annotator developed by the National Center for Biomedical Ontologies – NCBO, or cTakes developed by the Apache Software Foundation). … Cited by 1 Related articles All 4 versions

Multi-center colonoscopy quality measurement utilizing natural language processing TD Imler, J Morea, C Kahi, J Cardwell… – The American journal of …, 2015 – nature.com … Natural language processor. The Apache Software Foundation clinical Text Analysis and Knowledge Extraction System (cTAKES) (29) version 3.1.1 was utilized as the NLP engine for examination of colonoscopy and pathology reports. … Cited by 11 Related articles All 11 versions

Extraction of Disease Factors from Medical Texts RL Liu, SY Tung, YL Lu – Applied Artificial Intelligence, 2015 – Taylor & Francis … There have been natural language processing tools (eg, MetaMap 4 4 MetaMap is available at http://metamap.nlm.nih.gov/.View all notes. and cTAKES 5 5 cTAKES is available at http://ctakes.apache.org/.View all notes. ) that extract and recognize biomedical entities in texts. … Related articles All 2 versions

Automated prediction of risk for problem opioid use in a primary care setting TR Hylan, M Von Korff, K Saunders, E Masters… – The Journal of …, 2015 – Elsevier … programming language, version 2.7 (Python Software Foundation; http:www.python.org), modeled after the named entity recognition in the widely used Apache Clinical Text Analysis and Knowledge Extraction System (cTAKES; The Apache Software Foundation; http:www … Related articles All 11 versions

Increasing the efficiency of trial-patient matching: automated clinical trial eligibility Pre-screening for pediatric oncology patients Y Ni, J Wright, J Perentesis… – BMC medical …, 2015 – bmcmedinformdecismak. … … To summarize, the algorithm first extracted text-driven, term-level medical information (eg keywords and acronyms in Figure 1) from clinical narratives using the Apache clinical Text Analysis and Knowledge Extraction System (cTAKES) [36]. … Cited by 4 Related articles All 16 versions

Identification and progression of heart disease risk factors in diabetic patients from longitudinal electronic health records J Jonnagaddala, ST Liaw, P Ray… – BioMed research …, 2015 – downloads.hindawi.com … Savova et al. built a machine learning-based smoking classification module for cTAKES [16]. Goryachev et al. … The core NLP module adopted components from the OpenNLP package (v1.5.3) available at https://opennlp.apache.org/. … Cited by 3 Related articles All 11 versions

A Recommender System for Medical Imaging Diagnostic E MONTEIRO, F VALENTE, C COSTA… – Digital Healthcare …, 2015 – books.google.com … The Keyword Extractor uses the CTAKES framework [9] to annotate and extract clinical knowledge from these reports. From the annotations we get important keywords that describe reports main topics. … The information is indexed using Apache Lucene [10]. … Cited by 1 Related articles All 4 versions

Recognition And Normalization Of Biomedical Entities Within Clinical Notes André Alexandre Dias Leal Dissertaçao orientada pelo Prof. … Related articles All 4 versions

Classification of radiology reports for falls in an HIV study cohort J Bates, SJ Fodeh, CA Brandt… – Journal of the …, 2015 – jamia.oxfordjournals.org … Training, 4953, 396, 5349. Test, 2794, 145, 2939. Total, 7747, 541, 8288. Bag of Words and Concepts Model. We used YTEX, 13 an NLP tool built on top of Apache clinical Text Analysis and Knowledge Extraction System (cTAKES), 14 to extract features from each radiology report … Cited by 1 Related articles All 4 versions

Heart failure medications detection and prescription status classification in clinical narrative documents SM Meystre, Y Kim, J Heavirland… – Stud. Health Technol. …, 2015 – researchgate.net … Available at http://uima.apache.org [15] Levenshtein VI. Binary Codes Capable of Correcting Deletions, Insertions and Reversals. … Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications. … Cited by 2 Related articles All 4 versions

Dynamic Estimation of the Probability of Patient Readmission to the ICU using Electronic Medical Records K Caballero, R Akella – AMIA Annual Symposium Proceedings, 2015 – ncbi.nlm.nih.gov … Standard approaches used as proxy to estimate the probability of readmission, such as Apache III and SAPS II scores, do not … to the medical domain by annotating a set of discharge summaries using the Clinical Text Analysis and Knowledge Extraction System (cTAKES) 13 and … Related articles All 4 versions

Identifying risk factors for heart disease over time: overview of 2014 i2b2/UTHealth shared task Track 2 A Stubbs, C Kotfila, H Xu, Ö Uzuner – Journal of biomedical informatics, 2015 – Elsevier … The participants from the University of Utah [30], ranked 10th, used combinations of existing tools and their own regular expressions, along with the UMLS Metathesaurus 8 to identify risk factors, implemented in the Apache UIMA 9 framework. First, they used cTAKES’ built-in … Cited by 19 Related articles All 5 versions

Prediction of physiological subsystem failure and its impact in the prediction of patient mortality KC Barajas, R Akella – Big Data (Big Data), 2015 IEEE …, 2015 – ieeexplore.ieee.org … Also, we can differentiate patients with higher risk from the ones that are stable and improving to assign medical resources effectively. The prevailing medical practice relies on frameworks such as the Apache III [1], and SAPS II [2] scores. … Related articles All 2 versions

Semantic biomedical resource discovery: a Natural Language Processing framework P Sfakianaki, L Koumakis… – BMC medical …, 2015 – bmcmedinformdecismak. … … On the other hand, cTAKES, an Apache open source NLP system, implements rule-based and machine learning methods. The tool exhibits reasonable performance which was nevertheless inferior to the one achieved by MetaMap [23]. The purpose of the study. … Related articles All 15 versions

Taming Big Data: An Information Extraction Strategy for Large Clinical Text Corpora AV GUNDLAPALLI, G Divita, ME Carter… – Studies in health …, 2015 – books.google.com … elsewhere [6, 7]. Briefly, the V3NLP pipeline is APACHE UIMA-AS based and includes “best-of-breed” annotation components, including the cTAKES trained openNLP part-of-speech tagger and phraser, MetaMap phrase mapping to UMLS concepts, and NegexII negation. … Cited by 1 Related articles All 5 versions

Dynamically Modeling Patient’s Health State from Electronic Medical Records: A Time Series Approach KL Caballero Barajas, R Akella – Proceedings of the 21th ACM SIGKDD …, 2015 – dl.acm.org … We report an AUC 0.8657. Our proposed model clearly outperforms other methods of the literature in terms of sensitivity with 0.7885 compared to 0.6559 of Naive Bayes and F-score with 0.5929 compared to 0.4662 of Apache III score after 24 hours. … Cited by 14 Related articles

Using natural language processing to identify problem usage of prescription opioids DS Carrell, D Cronkite, RE Palmer, K Saunders… – International journal of …, 2015 – Elsevier … Fentanyl ADDICTION” were not differentiated). Our dictionary look up was modeled after that of the widely used Apache Clinical Text Analysis and Knowledge Extraction System (cTAKES) [32]. Like cTAKES, our system implemented … Cited by 7 Related articles All 5 versions

Detection of sentence boundaries and abbreviations in clinical narratives M Kreuzthaler, S Schulz – BMC medical …, 2015 – bmcmedinformdecismak. … … high coverage for CCDict. For the harvesting of the afore mentioned web resources we used Apache UIMA [20], for which tailored CollectionReaders were implemented. Support vector machines. Support vector machines [21 … Cited by 3 Related articles All 10 versions

DEEPEN: A negation detection system for clinical text incorporating dependency relation into NegEx S Mehrabi, A Krishnan, S Sohn, AM Roch… – Journal of biomedical …, 2015 – Elsevier … DepNeg was compared with cTAKES adoption of NegEx, which is customized to Mayo Clinic data. cTAKES is an open source natural language processing tool for information extraction from medical records developed by Mayo Clinic and released under Apache license [18]. … Cited by 4 Related articles All 8 versions

Distantly Supervised Information Extraction Using Bootstrapped Patterns S Gupta – 2015 – www-cs.stanford.edu Page 1. DISTANTLY SUPERVISED INFORMATION EXTRACTION USING BOOTSTRAPPED PATTERNS A DISSERTATION SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE AND THE COMMITTEE ON GRADUATE STUDIES OF STANFORD UNIVERSITY … Cited by 1 Related articles

Automated clinical trial eligibility prescreening: increasing the efficiency of patient identification for clinical trials in the emergency department Y Ni, S Kennebeck, JW Dexheimer… – Journal of the …, 2015 – jamia.oxfordjournals.org … information hidden within clinical narratives has been increasingly recognized as a critical component in describing a patient’s profile.29 , 30 , 35 Building on our experience with Mayo Clinic’s clinical Text Analysis and Knowledge Extraction System (cTAKES), we adapted it to … Cited by 7 Related articles All 10 versions

Automatic de-identification of case narratives from spontaneous reports in VigiBase J Sahlström – 2015 – diva-portal.org Page 1. UPTEC F 15054 Examensarbete 30 hp September 2015 Automatic de-identification of case narratives from spontaneous reports in VigiBase Jakob Sahlström Page 2. Page 3. Teknisk- naturvetenskaplig fakultet UTH-enheten … Related articles

Intelligent audit code generation from free text in the context of neurosurgery S Khademi, PD Haghighi, P Lewis, F Burstein… – acis2015.unisa.edu.au … cTAKES (Clinical Text Analysis and Knowledge Extraction System), (Savova et al. 2010) is an open-source NLP system developed at the Mayo Clinic using Apache UIMA and Apache Open NLP natural language processing toolkits. … Cited by 1 Related articles All 2 versions

[BOOK] Health Web Science K Denecke – 2015 – Springer Page 1. Health Information Science Health Web Science Kerstin Denecke Social Media Data for Healthcare Page 2. Health Information Science Series Editor Yanchun Zhang More information about this series at http://www.springer.com/series/11944 Page 3. Page 4. … Cited by 1 Related articles All 3 versions

Secondary use of electronic health records for building cohort studies through top-down information extraction M Kreuzthaler, S Schulz, A Berghold – Journal of biomedical informatics, 2015 – Elsevier … Raw data serves as input for the automated extraction for which the Apache Unstructured Information Management Architecture (UIMA 7 ) was used. … Elements within the highlighted area are in the scope of the Apache Unstructured Information Management Architecture. … Cited by 6 Related articles All 5 versions

Clinical element models in the SHARPn consortium TA Oniki, N Zhuo, CE Beebe, H Liu… – Journal of the …, 2015 – jamia.oxfordjournals.org … 2 messages, C-CDA documents, and text) from a file system or from external entities via the Nationwide Health Information Network and channel them to components of the normalization “pipeline” (step 2). The pipeline was based on the Apache Unstructured Information … Related articles All 8 versions

Adaptive semantic tag mining from heterogeneous clinical research texts T Hao, C Weng – Methods of information in medicine, 2015 – methods.schattauer.de … cTAKES [49] and Unstructured Informa- tion Management Architecture (UIMA) [50] both use such a component-based software architecture, although cTAKES works primarily with clinical notes and UIMA is for general-purpose text process- ing. … Cited by 2 Related articles All 6 versions

Ontology-based information extraction: identifying eligible patients for clinical trials in neurology P Geibel, M Trautwein, H Erdur, L Zimmermann… – Journal on Data …, 2015 – Springer … The Apache clinical Text Analysis and Knowledge Extraction System (cTAKES) [31] also pursues a linguistic approach to information extraction for documents, but is not tailored to documents written in German or to the problem of patient identification. … Cited by 6 Related articles All 3 versions

Maximizing clinical cohort size using free text queries AV Gundlapalli, D Redd, BS Gibson, M Carter… – Computers in biology …, 2015 – Elsevier … platform. No suitable search tools were found that supported negation assertions. Voogo is not an in depth NLP tool like V3NLP, HITEx, Sophia, cTAKES, etc. which are part of eMERGE, CHIR, and SHARP [33], [34], [35] and [36]. … Cited by 1 Related articles All 11 versions

Mining Electronic Health Records to Guide and Support Clinical Decision Support Systems J Jonnagaddala, HJ Dai, P Ray… – … through Clinical Decision …, 2015 – books.google.com … discharge summary notes presented in Figure 2 are processed to ex- tract part-of-speech tags using the cTAKES pipeline which … Big Data Technologies Big data technologies like Apache Hadoop provide a great opportunity for CDSS developers to overcome scalability and real … Cited by 5 Related articles All 3 versions

Text mining the EMR for modeling and predicting suicidal behavior among US veterans of the 1991 Persian Gulf War A Ben-Ari, K Hammond – System Sciences (HICSS), 2015 48th …, 2015 – ieeexplore.ieee.org … 8. http://lucene.apache.org/core/, accessed 6/15/2014. … 13. Savova, GK, Masanz, JJ, Ogren, PV, et al.: MMayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applicationsP, J Am Med Inform Assoc, 2010, 17, (5), pp. … Cited by 1 Related articles All 4 versions

Development of phenotype algorithms using electronic medical records and incorporating natural language processing KP Liao, T Cai, GK Savova, SN Murphy, EW Karlson… – bmj, 2015 – bmj.com … The i2b2 project used two open source, NLP software systems to extract concepts: the Health information Text Extraction system and the Apache clinical Text Analysis and Knowledge Extraction System21 (table 1). Methods used to develop EMR phenotype algorithms. … Cited by 15 Related articles All 9 versions

Ontology-based data integration between clinical and research systems S Mate, F Köpcke, D Toddenroth, M Martin… – PloS one, 2015 – journals.plos.org Data from the electronic medical record comprise numerous structured but uncoded ele-ments, which are not linked to standard terminologies. Reuse of such data for secondary research purposes has gained in importance recently. However, the identification of rele-vant data elements … Cited by 13 Related articles All 13 versions

Topic Models and Dynamic Prediction Models and their applications in Document Retrieval and Healthcare KL Caballero Barajas – 2015 – escholarship.org Page 1. … Related articles All 3 versions

Efficient and sparse feature selection for biomedical text classification via the elastic net: Application to ICU risk stratification from nursing notes BJ Marafino, WJ Boscardin, RA Dudley – Journal of biomedical informatics, 2015 – Elsevier Sparsity is often a desirable property of statistical models, and various feature selection methods exist so as to yield sparser and interpretable models. Howev. Cited by 6 Related articles All 7 versions

Natural language processing and data mining for clinical text K Raja, SR Jonnalagadda – Healthc. Data Anal, 2015 – books.google.com … apache. … The Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES)[85], Special Purpose Radiology Understanding System (SPRUS)[33], SymText (Symbolic Text Processor)[39], and SPECIALIST language-processing system [66] are the major systems … Cited by 4 Related articles

Technology Roadmap Development for Big Data Healthcare Applications S Zillner, S Neururer – KI-Künstliche Intelligenz, 2015 – Springer … Perspect Health Inf Manag. 35. Savova GK, Masanz JJ, Ogren PV, Zheng J, Sohn S, Kipper-Schuler KC, Chute CG (2010) Mayo clinical text analysis and knowledge extraction system (cTAKES): architecture, component evaluation and applications. … Cited by 3 Related articles All 2 versions

The fully automated construction of metabolic pathways using text mining and knowledge-based constraints JM Czarnecki – 2015 – bbktheses.da.ulcc.ac.uk Page 1. Thesis submitted for the degree of Doctor of Philosophy The fully automated construction of metabolic pathways using text mining and knowledge-based constraints. Jan Michael Czarnecki Birkbeck, University of London 3rd May, 2015 Page 2. … Related articles All 2 versions

Health Analytics and Predictive Modeling: Four Essays on Health Informatics YK Lin – 2015 – arizona.openrepository.com Page 1. HEALTH ANALYTICS AND PREDICTIVE MODELING: FOUR ESSAYS ON HEALTH INFORMATICS by Yu-Kai Lin _____ A Dissertation Submitted to the Faculty of the DEPARTMENT OF MANAGEMENT INFORMATION SYSTEMS … Related articles

A multi-ontology approach to annotate scientific documents based on a modularization technique AM de Carvalho Moura, MC Cavalcanti – Journal of biomedical …, 2015 – Elsevier Scientific text annotation has become an important task for biomedical scientists. Nowadays, there is an increasing need for the development of intelligent syst. Related articles All 5 versions

KneeTex: an ontology–driven system for information extraction from MRI reports I Spasi?, B Zhao, CB Jones… – Journal of …, 2015 – jbiomedsem.biomedcentral.com Skip to main content. Advertisement. Biomed Central logo Menu. Search Search. Publisher main menu. … Cited by 3 Related articles All 18 versions

Mining the Biomedical Literature C Mihaila, R Batista-Navarro, N Alnazzawi… – Healthcare Data …, 2015 – books.google.com Page 280. Chapter 8 Mining the Biomedical Literature Claudiu Mihaila National Centre for Text Mining University of Manchester Manchester, UK claudiu. mihaila@ manchester. ac. uk Riza Batista-Navarro National Centre for … Cited by 1 Related articles

Context-specific Consistencies in Information Extraction P Klügl – opus.uni-wuerzburg.de Page 1. P eter Klügl Context-specific Consistencies in Information Extraction Peter Klügl Rule-based and Probabilistic Approaches C ontext-specific C on sistencies in Inform ation Extraction Page 2. Peter Klügl Context-specific Consistencies in Information Extraction Page … Related articles All 4 versions