Apache cTAKES 2017


Notes:

cTAKES stands for “clinical Text Analysis and Knowledge Extraction System”.

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

Wikipedia:

References:

See also:

100 Best Apache Giraph Videos | 100 Best Apache Hadoop Videos | 100 Best Apache Lucene Videos | 100 Best Apache Mahout Videos | 100 Best Apache Oozie Videos | 100 Best Apache OpenNLP Videos | 100 Best Apache Pig Videos | 100 Best Apache Sqoop Videos | Apache OpenNLP & Coreference Resolution 2016 | Apache OpenNLP 2016 | Apache OpenNLP & Dialog Systems | Apache Tika


A Natural language processing framework for assessing hospital readmissions for patients with COPD
A Agarwal, C Baechle, R Behara… – IEEE journal of …, 2017 – ieeexplore.ieee.org
… Biomedical and Health Informatics 3) Prediction of 30 day readmission using EHR using Apache cTAKES Recent research by Duggal et al. uses Apache cTAKES to annotate the unstructured EHR [28] … This higher level feature extraction is done using Apache cTAKES …

Big data driven co-occurring evidence discovery in chronic obstructive pulmonary disease patients
C Baechle, A Agarwal, X Zhu – Journal of Big Data, 2017 – Springer
… Apache cTAKES is leveraged to annotate and structure clinical notes. Several extensions to cTAKES have been written to parallelize the annotation of large sets of clinical notes … UMLS contains medical terms from many data sources in a standardized format. Apache cTAKES …

Automatic prediction of coronary artery disease from clinical narratives
K Buchan, M Filannino, Ö Uzuner – Journal of biomedical informatics, 2017 – Elsevier
… We concluded that coverage was comparable in the two populations using the z-test (? 0.05 ). 3. Methods. Our system processes records using Apache cTAKES, an NLP system for extracting information from clinical free-text [32] …

Integration of Knowledge Extracted from Clinical Notes with Patient Reported Outcomes and Genetic Reports for Advancing Research into Phelan-McDermid …
C Kothari, M Wack, CH Khodja, S Finan, G Savova… – transmartfoundation.org
… 3. The MITRE MIST scrubber and the Scrubber toolkit in the Apache cTAKES Natural Language Processing (NLP) engine erased Protected Health Information. 4.The Apache cTAKES NLP engine extracted knowledge from anonymized …

Phelan?McDermid syndrome data network: Integrating patient reported outcomes with clinical notes and curated genetic reports
C Kothari, M Wack, C Hassen?Khodja… – American Journal of …, 2017 – Wiley Online Library
… Then, the MITRE 2 | KOTHARI ET AL. Page 3. MIST tool (Aberdeen et al., 2010) and the Scrubber toolkit (McMurry, Fitch, Savova, Kohane, & Reis, 2013) in the Apache cTAKES NLP engine were used to erase Protected Health Information (PHI) elements from the text …

DeepPhe: A Natural Language Processing System for Extracting Cancer Phenotypes from Clinical Records
GK Savova, E Tseytlin, S Finan, M Castine, T Miller… – Cancer research, 2017 – AACR
Skip to main content. AACR Publications: Cancer Discovery; Cancer Epidemiology, Biomarkers & Prevention; Cancer Immunology Research; Cancer Prevention Research; Cancer Research; Clinical Cancer Research; Molecular Cancer Research; Molecular Cancer Therapeutics …

UEvora at CLEF eHealth 2017 Task 3
H Yang, T Gonçalves – ceur-ws.org
… Apache cTAKES is an open source natural language processing system for ex- traction of information from electronic medical record clinical free-text [2]. It includes following components: – Sentence boundary detector – Tokenizer – Normalizer 1 http://ctakes.apache.org/index …

A framework for the estimation and reduction of hospital readmission penalties using predictive analytics
C Baechle, A Agarwal – Journal of Big Data, 2017 – Springer
… Clinical NLP software. Apache cTAKES is an open source Clinical NLP tool created and maintained by the Mayo Clinic [30]. Apache cTAKES annotates clinical notes using domain specific dictionaries and clinically trained NLP models …

Hitachi at SemEval-2017 Task 12: System for temporal information extraction from clinical notes
PR Sarath, R Manikandan, Y Niwa – Proceedings of the 11th …, 2017 – aclweb.org
… 1) Stanford-CoreNLP (Manning et al., 2014) 2) scikit-learn (Pedregosa et al., 2011) 3) NLTK (Loper and Bird, 2002) 4) XGBoost (Chen and Guestrin, 2016) 5) Apache CTAKES (Savova et al., 2010) 6) ClearTK (Bethard et al., 2014) 7) H2O1 2.1 Time span identification …

Towards generalizable entity-centric clinical coreference resolution
T Miller, D Dligach, S Bethard, C Lin… – Journal of biomedical …, 2017 – Elsevier
… A performance-optimized version of the mention-synchronous system will be included in the open source Apache cTAKES software. Graphical abstract … We start by running a dependency parser on the entire corpus (the clinically trained parser in Apache cTAKES) …

Co-occurring evidence discovery for COPD patients using natural language processing
C Baechle, A Agarwal, R Behara… – Biomedical & Health …, 2017 – ieeexplore.ieee.org
… 321 Page 2. Our research makes use of Apache cTAKES and has written the code necessary to annotate document aggregations. The Unified Medical Language System (UMLS) is a set of medical dictionaries maintained by the National Library of Medicine (NLM) …

Unsupervised Domain Adaptation for Clinical Negation Detection
T Miller, S Bethard, H Amiri, G Savova – BioNLP 2017, 2017 – aclweb.org
… We make use of the (Wu et al., 2014) sys- tem in these experiments, as it is freely available as part of the Apache cTAKES (Savova et al., 2010)1 clinical NLP software, and can be easily retrained … 1http://ctakes.apache.org 166 Page 3 …

Acronym disambiguation in spanish electronic health narratives using machine learning techniques
I Rubio-López, R Costumero, H Ambit… – Studies in health …, 2017 – books.google.com
… I. Rubio-López et al./Acronym Disambiguation in Spanish Electronic Health Narratives 252 Some successful approaches in this context of clinical settings are Apache cTAKES [3] and MetaMap [4]. Acronyms allow the physicians to speed-up the writing process minimizing the …

Semi-Automatic Terminology Generation for Information Extraction from German Chest X-Ray Reports.
J Krebs, H Corovic, G Dietrich, M Ertl… – Studies in health …, 2017 – books.google.com
… Some well- known systems for clinical information extraction are HITEx ([6]; based on GATE) and Apache cTAKES ([7]; based on UIMA). We used a special IE pipeline similar to [4] based on UIMA consisting of the following main steps for reports: 1. Anonymization (if necessary) …

Correlating lab test results in clinical notes with structured lab data: A case study in hba1c and glucose
L Sijia, W Liwei, D Ihrke, V Chaudhary… – AMIA Summits on …, 2017 – ncbi.nlm.nih.gov
… Apache cTAKES 9 , originated from OHNLP Mayo cTAKES, has been adopted widely and has influenced the whole clinical informatics community. Lab tests are medical procedures used to establish or confirm a diagnosis and aid the management of disease 10 …

Medical documents processing for summary generation and keywords highlighting based on natural language processing and ontology graph descriptor approach
A Dudko, T Endrjukaite, Y Kiyoki – Proceedings of the 19th International …, 2017 – dl.acm.org
… In this research we use Apache cTAKES [11] a natural language processing system for extraction of information from electronic medical record clinical free-text to process documents and to identify keywords in the text of the document related to medical domain …

Annotating the Clinical Text–MiPACQ, ShARe, SHARPn and THYME Corpora
G Savova, S Pradhan, M Palmer, W Styler… – Handbook of Linguistic …, 2017 – Springer
… Several NLP components were built using the MiPACQ corpus [14, 15, 88] – POS tagger, constituency parser, dependency parser and SRL – which were released as a part of Apache cTAKES … The best performing methods are released as modules within Apache cTAKES …

A long journey to short abbreviations: developing an open-source framework for clinical abbreviation recognition and disambiguation (CARD)
Y Wu, JC Denny, S Trent Rosenbloom… – Journal of the …, 2017 – academic.oup.com
… from discharge summaries, CARD achieved an F1 score of 0.755 for identifying and disambiguating all abbreviations in a corpus from the VUMC discharge summaries, which is superior to MetaMap and Apache’s clinical Text Analysis Knowledge Extraction System (cTAKES) …

NeuroNER: an easy-to-use program for named-entity recognition based on neural networks
F Dernoncourt, JY Lee, P Szolovits – arXiv preprint arXiv:1705.05487, 2017 – arxiv.org
… rely on CRFs. GAPSCORE uses SVMs (Chang et al., 2004). Apache cTAKES (Savova et al., 2010) and Gate’s ANNIE (Cunningham et al., 1996; May- nard and Cunningham, 2003) use mostly rules. NeuroNER, the first ANN …

Classification based extraction of numeric values from clinical narratives
M Zubke – Proceedings of the Biomedical NLP Workshop …, 2017 – lml.bas.bg
… the process of information extraction. Be- sides MedLEE (Friedman et al., 1995), Apache cTakes (Savova et al., 2010) is such a software solution that combines the concepts, mentioned above. It should be noticed, that many …

Medical diagnosis as a linguistic game
P Fritz, A Kleinhans, F Kuisle… – BMC medical …, 2017 – bmcmedinformdecismak …
Skip to content Advertisement …

CLAMP–a toolkit for efficiently building customized clinical natural language processing pipelines
E Soysal, J Wang, M Jiang, Y Wu… – Journal of the …, 2017 – academic.oup.com
… CLAMP is implemented in Java as a desktop application. It builds on the Apache Unstructured Information Management Architecture ™ (UIMA) framework 17 to maximize its interoperability with other UIMA-based systems such as cTAKES …

Sharing Annotated Audio Recordings of Clinic Visits With Patients—Development of the Open Recording Automated Logging System (ORALS): Study …
PJ Barr, MD Dannenberg, CH Ganoe… – JMIR research …, 2017 – ncbi.nlm.nih.gov
… concepts and their corresponding classes. For this named-entity recognition task we will use Apache cTAKES information extraction framework [64] and Unified Medical Language System (UMLS) [65]. cTAKES is open-source …

A Clinical Decision Support System for the Identification of Potential Hospital Readmission Patients
C Baechle – 2017 – fau.digital.flvc.org
… 38 Figure 3.4 cTAKES Components ….. 42 … 93 Figure 4.9 Big Data Version of COED as Implemented in the Hadoop Ecosystem Using Apache Spark ….. 94 …

Latent topic ensemble learning for hospital readmission cost reduction
C Baechle, A Agarwal, R Behara… – Neural Networks (IJCNN) …, 2017 – ieeexplore.ieee.org
… CD Feature Extraction In our experiments, discharge summaries are annotated using Apache cTAKES. Annotations containing diseases & disorders, medications, and anatomical site are used. Annotations are normalized to a UMLS CID to increase the quality of features …

Aligned-ayer Text Search in Clinical Notes
S Wua, A Wena, Y Wangb, S Liub, H Liub – 2017 – researchgate.net
… For example, in Figure 2, L2 is named entities, and = , , , , C0032961, C0151526, C0011209, …. The artifacts are aligned with the base layer by storing 2 additional numbers: 1 http://ctakes.apache.org start index and length …

Using Real-Wolrd Healthcare Data To Define And Prevent Complications In Inflammatory Bowel Disease
A Anderson – 2017 – d-scholarship.pitt.edu
… Apache openNLP natural language toolkit and Apache cTakes natural language processing (NLP) system for extraction of information from clinical free-text to improve the processing of natural language text.47,48 There are several major challenges to extracting meaningful …

Stacking with Auxiliary Features for Entity Linking in the Medical Domain
NF Rajani, M Bornea, K Barker – BioNLP 2017, 2017 – aclweb.org
… cTAKES: Apache cTAKES3 is an open source entity recognition system, originally developed at Mayo Clinic for identifying UMLS concepts in electronic medical records … 2MetaMap: http://metamap.nlm.nih.gov/ 3cTAKES: https://ctakes.apache.org …

Evaluating and improving annotation tools for medical forms
YC Lin, V Christen, A Groß, SD Cardoso… – … Conference on Data …, 2017 – Springer
… 2.2 cTAKES. cTAKES 3 is built on the Apache UIMA framework 4 providing a standardized architecture for processing unstructured data … 3. Clinical Text Analysis and Knowledge Extraction System http://ctakes.apache.org. 4 …

Annotating Mentions of Coronary Artery Disease in Medical Reports
L Tonin – 2017 – diva-portal.org
… IBM produced the UIMA pipeline and has since donated the source code to the Apache Software Foundation, the source code is now open to NLP communities. The Apache Software Foundation is an open source community of developers …

Clinical information extraction applications: A literature review
Y Wang, L Wang, M Rastegar-Mojarad, S Moon… – Journal of biomedical …, 2017 – Elsevier
With the rapid adoption of electronic health records (EHRs), it is desirable to harvest information and knowledge from EHRs to support automated systems at the.

Distant Supervision with Transductive Learning for Adverse Drug Reaction Identification from Electronic Medical Records
S Taewijit, T Theeramunkong, M Ikeda – Journal of healthcare …, 2017 – hindawi.com
… Many researchers endeavor to deal with medical NER and normalization by developing computational tools such as cTAKES (http://ctakes.apache.org), FreeLing-Med, MetaMap (https://metamap.nlm.nih.gov), MedLEE (http://www.medlingmap.org/taxonomy/term/80), tmChem …

Neural temporal relation extraction
D Dligach, T Miller, C Lin, S Bethard… – Proceedings of the 15th …, 2017 – aclweb.org
… 2015 test set (Lin et al., 2016b). This system is available as part of cTAKES (http: //ctakes.apache.org) and performs both event- event and event-time relation classification. We discard all non-contains relation instances from …

Identification of Risk Factors in Clinical Texts through Association Rules
S Boytcheva, I Nikolova, G Angelova… – Proceedings of the …, 2017 – lml.bas.bg
… lation fitted in the moderate category. The main limitation was the lack of a systematic evaluation of the developed text mining system. In (Harpaz 2Official site http://ctakes. apache. org/ 65 Page 74. et al., 2014) the authors state …

Evaluating and Improving Annotation Tools for Medical Forms
C Pruski, M Da Silveira, E Rahm – Data Integration in the Life …, 2017 – books.google.com
… WSD selects the concept that is semantically most consistent with the surrounding text [12]. 2.2 cTAKES cTAKES3 is built on the Apache UIMA framework4 providing a standardized architecture for processing unstructured data …

A Review of Existing Applications and Techniques for Narrative Text Analysis in Electronic Medical Records
A Pomares-Quimbaya, RA Gonzalez… – Artificial Intelligence …, 2017 – igi-global.com
… cTAKES (Open-Source Apache Clinical Text Analysis and Knowledge Extraction System): An NLP platform with components specifically trained on clinical text. Each one has unique quali- ties and capabilities and includes at least one analysis engine (annotator) …

MetaMap Lite: an evaluation of a new Java implementation of MetaMap
D Demner-Fushman, WJ Rogers… – Journal of the American …, 2017 – academic.oup.com
… and clinical text, MetaMap Lite demonstrated real-time speed and precision, recall, and F 1 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 …

Adverse drug event discovery using biomedical literature: a big data neural network adventure
AP Tafti, J Badger, E LaRose, E Shirzadi… – JMIR medical …, 2017 – ncbi.nlm.nih.gov
… All tiers developed on top of the Apache Spark 2.0 that utilizes an Elasticsearch database 2.4.1 to data storage and retrieval … Once we have the labeled sentences as ADEs or No-ADEs, we focus on ADE sentences and find the positive adverse-drug interactions using cTAKES [64 …

Detection of Adverse Drug Reaction from Twitter Data
MS Ye Ye, MS Diyang Xue, MS Fan Mi, MS Utkars Jain – ceur-ws.org
… 7. Meng X, Bradley J, Yavuz B, et al. [seminal] MLlib: Machine Learning in Apache Spark. J Mach Learn Res … Savova GK, Masanz JJ, Ogren PV, et al. Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications …

CREATE: Clinical REcords Analysis Technology Ensemble
A Dekhtyara, S Durstb, V Kaganb, A Stevensb… – joshterrell.com
… cTAKES Features. As mentioned in Section 2, Apache cTAKES is a framework for extracting a variety of information from medical records. cTAKES looks for terminology related to medical symptoms, mentions of medications, body parts, 1https://code.google.com/p/word2vec/ 12 …

Integrating Data Analysis Tools for Better Treatment of Diabetic Patients
S Boytcheva, G Angelova, Z Angelov, D Tcharaktchiev – 2017 – ceur-ws.org
… increases the number of patients in the considered cohorts and thus increases the 1 http://ctakes.apache.org/ sensitivity of the recognition. Despite the NLP limitations, the conclusion is that NLP engines are powerful components …

HealthRecSys: A semantic content-based recommender system to complement health videos
CLS Bocanegra, JLS Ramos… – BMC medical …, 2017 – bmcmedinformdecismak …
… We conducted a text analysis using the Unified Medical Language System (UMLS) 6 with SNOMED-CT annotations to match the cTAKES framework … 7 Appendix 1 shows the configuration used to run the cTAKES execution …

Automated Radiology Report Summarization Using an Open-Source Natural Language Processing Pipeline
DJ Goff, TW Loehfelm – Journal of digital imaging, 2017 – Springer
… available in the reference on- tology is useful. The open-source Apache project Clinical Text Analysis and Knowledge Extraction System (cTAKES) is one such hybrid tool. cTAKES uses machine learning for some components, such …

The Acquisition and Analysis of Electroencephalogram Data for the Classification of Benign Partial Epilepsy of Childhood with Centrotemporal Spikes
JA Scarborough – 2017 – repository.usfca.edu
… Research pursued by CHIP includes Health Data Fusion, SMART Health IT, HealthMap, and Apache cTakes. Each of these endeavors requires significant amounts of health data (sometimes millions of patient records) and the infrastructure necessary to obtain, process, and …

Semantic annotation in biomedicine: the current landscape
J Jovanovi?, E Bagheri – Journal of …, 2017 – jbiomedsem.biomedcentral.com
… Allie – a search service for abbreviations and their long forms (http://allie.dbcls.jp/). Table 3 General purpose biomedical semantic annotation tools (Part I). cTAKES [4]. NOBLE Coder [20] … Availability. open source; available under Apache License, v.2.0. open-source; …

Large-scale identification of patients with cerebral aneurysms using natural language processing
VM Castro, D Dligach, S Finan, S Yu, A Can… – Neurology, 2017 – AAN Enterprises
Skip to main page content …

Computer science, biology and biomedical informatics academy: outcomes from 5 years of immersing high-school students into informatics research
AJ King, AM Fisher, MJ Becich… – Journal of pathology …, 2017 – ncbi.nlm.nih.gov
… The NLP software Apache cTAKES™ was used to extract clinical mentions of features. Then, a Boolean occurrence table was created with columns indicating clinical terms and rows indicating the terms’ mention per patient …

Structuring Legacy Pathology Reports by openEHR Archetypes to Enable Semantic Querying
S Kropf, P Krücken, W Mueller… – Methods of information …, 2017 – thieme-connect.com
… J, Brandt C. The Yale cTAKES extensions for document classification: architecture and application. J Am Med Inform Assoc. 2011; 18 (05) 614-620. 24 General Architecture for Text Engeneering [cited 2016 Nov 09]. Available from: http://gate.ac.uk/. 25 Apache UIMA [cited 2016 …

Mining comorbidity patterns using retrospective analysis of big collection of outpatient records
S Boytcheva, G Angelova, Z Angelov… – … information science and …, 2017 – Springer
… Footnotes. 1. Clinical Text Analysis and Knowledge Extraction System: http://ctakes.apache. org/. 2. International Classification of Diseases and Related Health Problems 10th Revision. http://apps.who.int/classifications/icd10/browse/2015/en. 3 …

Medical Entity and Relation Extraction from Narrative Clinical Records in Italian Language
G De Pietro – … Interactive Multimedia Systems and Services 2017, 2017 – books.google.com
… The cTAKES showed a high performance in medical concept extraction, making it suitable for succes- sive applications [16, 20] … 11.0 has been used, in consideration of its capabilities of analyzing unstructured text [2]. It is based on the Apache UIMA Page 141 …

RysannMD: A biomedical semantic annotator balancing speed and accuracy
J Cuzzola, J Jovanovi?, E Bagheri – Journal of biomedical informatics, 2017 – Elsevier
… with respect to the state of the art biomedical semantic annotators, we have conducted a series of experiments using standard benchmarking corpora, including both gold and silver standards, and four modern biomedical semantic annotators, namely cTAKES, MetaMap, NOBLE …

Supporting Families in Reviewing and Communicating about Radiology Imaging Studies
MK Hong, C Feustel, M Agnihotri, M Silverman… – Proceedings of the …, 2017 – dl.acm.org
… demonstrated an integrated radi- ology patient portal interface which uses the cTAKES knowledge extraction NLP module [1] to automatically identify and extract medical concepts from the Impression section of an unstructured report [2]. In addition to provid- ing lay and clinician …

Medical Entity and Relation Extraction from Narrative Clinical Records in Italian Language
C Diomaiuta, M Mercorella, M Ciampi… – … Conference on Intelligent …, 2017 – Springer
… The cTAKES showed a high performance in medical concept extraction, making it suitable for successive applications [16, 20] … 11.0 has been used, in consideration of its capabilities of analyzing unstructured text [2]. It is based on the Apache UIMA framework …

Semantic annotation of electronic health records in a multilingual environment
LFL Campos – 2017 – repositorio.ul.pt
Page 1. UNIVERSIDADE DE LISBOA FACULDADE DE CIÊNCIAS DEPARTAMENTO DE BIOLOGIA VEGETAL Semantic annotation of electronic health records in a multilingual environment Luís Filipe Leal Campos DISSERTAÇÃO …

A semantic-based workflow for biomedical literature annotation
P Sernadela, JL Oliveira – Database, 2017 – academic.oup.com
Abstract. Computational annotation of textual information has taken on an important role in knowledge extraction from the biomedical literature, since most of.

Semantic Technologies for Re-Use of Clinical Routine Data.
M Kreuzthaler, C Martínez-Costa… – Studies in health …, 2017 – books.google.com
… Research institutions that have considerable merits in clinical NLP are the Mayo Clinic [5](cTakes), the Veterans Affairs network of hospitals [1, 6](The Leo framework-The VINCI-developed NLP infrastructure using UIMA [17], the Apache Unstructured Information Management …

Medical subdomain classification of clinical notes using a machine learning-based natural language processing approach
WH Weng, KB Wagholikar… – BMC medical …, 2017 – bmcmedinformdecismak …
… To extract and represent interpretable clinical features, we adopted the clinical NLP annotator and parser, Apache clinical Text Analysis and Knowledge Extraction System (cTAKES) [34], and used the UMLS Metathesaurus, and Semantic Network to filter clinically relevant …

Large?scale extraction of drug–disease pairs from the medical literature
P Wang, T Hao, J Yan, L Jin – Journal of the Association for …, 2017 – Wiley Online Library
… If negation is not taken into account, some relations of pairs are wrong, such as “Prognostic evaluation of cases of Myocardial Infarction not treated with Anticoagulants.” Here, we use a medical natural language processing system tool, cTAKES3, to recognize the negative …

Knowledge-driven entity recognition and disambiguation in biomedical text
A Siu – 2017 – publikationen.sulb.uni-saarland.de
Page 1. Saarland University Faculty of Mathematics and Computer Science Department of Computer Science Knowledge-driven Entity Recognition and Disambiguation in Biomedical Text Amy Siu A dissertation submitted towards the degree Doctor of Engineering …

Machine Learning and Knowledge Extraction in Digital Pathology Needs an Integrative Approach
H Müller, R Reihs, K Zatloukal – … , Banff, AB, Canada, July 24-26 …, 2017 – books.google.com
Page 27. Machine Learning and Knowledge Extraction in Digital Pathology Needs an Integrative Approach Andreas Holzinger1 (B), Bernd Malle1, 2, Peter Kieseberg1, 2, Peter M. Roth3, Heimo Müller1, 4, Robert Reihs1, 4, and …

Machine Learning and Knowledge Extraction in Digital Pathology Needs an Integrative Approach
A Holzinger, B Malle, P Kieseberg, PM Roth… – … Machine Learning and …, 2017 – Springer
During the last decade pathology has benefited from the rapid progress of image digitizing technologies, which led to the development of scanners, capable to produce so-called Whole Slide images (WSI).

Effective Information Extraction Framework for Heterogeneous Clinical Reports Using Online Machine Learning and Controlled Vocabularies
S Zheng, JJ Lu, N Ghasemzadeh, SS Hayek… – JMIR medical …, 2017 – ncbi.nlm.nih.gov
… [PMC free article] [PubMed] [Cross Ref]. 8. Savova G, Masanz JJ, Ogren PV, Zheng J, Sohn S, Kipper-Schuler KC, Chute CG. Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications … Apache. [2017-04-20] …

A Study on Data Analytics: Internet of Things & Health-Care
N Nalini, P Suvithavani – 2017 – pdfs.semanticscholar.org
… One of the examples of clinical text mining tool is clinical Text Analysis and Knowledge Extraction System (cTAKES) … Apache Hadoop[5] offer Hadoop Distributed File System storage which takes care of distributed storage and fault tolerance …

Pdd graph: Bridging electronic medical records and biomedical knowledge graphs via entity linking
M Wang, J Zhang, J Liu, W Hu, S Wang, X Li… – International Semantic …, 2017 – Springer
… We publish the PDD graph as an open resource 2 , and provide a SPARQL query endpoint using Apache Jena Fuseki 3 … PV, Zheng, J., Sohn, S., Kipper-Schuler, KC, Chute, CG: Mayo clinical text analysis and knowledge extraction system (cTAKES): architecture, component …

Discriminative and distinct phenotyping by constrained tensor factorization
Y Kim, R El-Kareh, J Sun, H Yu, X Jiang – Scientific reports, 2017 – nature.com
… algorithm. We evaluated discriminative power of our models with an Intensive Care Unit database (MIMIC-III) and demonstrated superior performance than state-of-the-art ICU mortality calculators (eg, APACHE II, SAPS II). Example …

Evaluation of lexicon-and syntax-based negation detection algorithms using clinical text data
J Manimaran, T Velmurugan – Bio-Algorithms and Med-Systems, 2017 – degruyter.com
… algorithm called dependency parser-based negation (DepNeg) showed that their F-score of 83% is slightly higher than the cTAKES negation module … The older version of NegEx did not use the possible conjunctions phrases, but the latest version, Apache 2.0, is upgraded with …

Information extraction with neural networks
JY Lee – 2017 – dspace.mit.edu
Page 1. Information Extraction with Neural Networks by Ji Young Lee Submitted to the Department of Electrical Engineering and Computer Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science at the …

Social network analysis in healthcare
K Baktha, M Dev, H Gupta, A Agarwal… – Internet of Things and …, 2017 – Springer
… cTakes is a natural language processing system for extraction of information from electronica medical record clinical free-text. It was built using the Apache UIMA (Unstructured Information Management Architecture). Another interesting tool is HealthMap …

Unlocking echocardiogram measurements for heart disease research through natural language processing
OV Patterson, MS Freiberg… – BMC …, 2017 – bmccardiovascdisord.biomedcentral …
… The natural language processing (NLP) system was built using Leo, [9] a set of services and libraries that facilitate the rapid creation and deployment of NLP algorithms using the Apache Unstructured Information Management Architecture Asynchronous Scaleout (UIMA AS …

Clinical documentation variations and NLP system portability: a case study in asthma birth cohorts across institutions
S Sohn, Y Wang, CI Wi, EA Krusemark… – Journal of the …, 2017 – academic.oup.com
AbstractObjective. To assess clinical documentation variations across health care institutions using different electronic medical record systems and investigat.

A novel tool for the identification of correlations in medical data by faceted search
D Schmidt, K Budde, D Sonntag, HJ Profitlich… – Computers in biology …, 2017 – Elsevier
… Well-known English-language systems are cTAKES [11], HITEx [12,13] and IBM’s MedKAT [14] … The pipeline has been implemented in the Apache UIMA (Unstructured Information Management Architecture) framework, a framework for analysis of unstructured data such as text …

Natural language processing systems for capturing and standardizing unstructured clinical information: A systematic review
K Kreimeyer, M Foster, A Pandey, N Arya… – Journal of biomedical …, 2017 – Elsevier
Skip to main content …

Mining electronic health records to guide and support clinical decision support systems
J Jonnagaddala, HJ Dai, P Ray… – Healthcare Ethics and …, 2017 – 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 …

A technique to detect multi-grained code clones
Y Yuki, Y Higo, S Kusumoto – Software Clones (IWSC), 2017 …, 2017 – ieeexplore.ieee.org
… files LOC Any23 369 46,957 cTAKES 1253 209,545 Forrest 252 32,491 JSPWiki 491 107,530 jUDDI 938 163,103 Onami 572 43,784 OODT 1,628 223,846 OpenOffice 3871 774,670 Roller 612 96,617 Wink 1,372 210,167 Sum 11,358 1,908,710 1http://svn.apache.org/repos/asf …

Yleiskäyttöinen tekstinluokittelija suomenkielisille potilaskertomusteksteille
E Pursiainen – 2017 – aaltodoc.aalto.fi
Page 1. Aalto University School of Science Life Science Technologies Eetu Pursiainen General Purpose Text Classifier for Finnish Medical Texts Master’s Thesis Espoo, October 23rd, 2017 Supervisor: Professor Juho Rousu, Aalto University Advisors: D.Sc …

Metabolic pathway mining
JM Czarnecki, AJ Shepherd – Bioinformatics, 2017 – Springer
… 4.1 General Text-Mining Tools. Libraries written in most programming languages exist for carrying out basic NLP tasks such as sentence parsing and part-of-speech tagging. One toolkit was found to fit our criteria: Apache OpenNLP [39] …

A Multi API approach for Natural Language Processing in Unstructured Clinical Documents
H Krimpen – 2017 – dspace.library.uu.nl
… 23 3.1.4 General clinical NLP system . . . . . 25 3.1.5 HITEx . . . . . 26 3.1.6 cTakes . . . . . 26 3.1.7 ClearTK . . . . . 28 3.1.8 Health-CPS …

Application of text information extraction system for real-time cancer case identification in an integrated healthcare organization
F Xie, J Lee, CE Munoz-Plaza… – Journal of Pathology …, 2017 – jpathinformatics.org
… and disk space allocation for data storage; (2) third-party software installed were JAVA, MySQL database server, Tomcat web server, Apache Ant, and … Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): Architecture, component evaluation and applications …

A Semantically Rich Cognitive Search Assistant for Clinical Notes
CT Grasso – 2017 – search.proquest.com
… CRF conditional random fields. cTAKES clinical Text Analysis and Knowledge Extraction System. CUI concept unique identifier … cTakes – Mayo clinical Text Analysis and Knowledge Extraction System: cTakes was developed in conjunction with the Mayo Clinic, which is one of …

The cloud4health Project: Secondary Use of Clinical Data with Secure Cloud-Based Text Mining Services
J Fluck, P Senger, W Ziegler, S Claus… – … and Algorithms in …, 2017 – Springer
… the SHARPn project [44]. In SHARPn tools and resources are developed that influence and extend secondary uses of clinical data [7]. One of the information extraction tools provided by SHARPn is cTAKES [41]. It is developed …

Advances in Health Education Technology
A Reynolds, TF Osborne, J Waggoner… – Using Technology to …, 2017 – books.google.com
Page 303. 13 Advances in Health Education Technology Ashley Reynolds, Thomas F. Osborne, John Waggoner, Renee Melton, Ramin Motarjemi, Jürgen P. Schulze, and Diane Chau The passing of knowledge from one to another is a practice as old as time …

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