Apache cTAKES & Clinical Dialog Systems

Notes:

cTAKES (clinical Text Analysis and Knowledge Extraction System) is a natural language processing (NLP) system that is used to extract relevant information from electronic medical records and other clinical documents.

cTAKES is designed to automatically identify and extract important information from clinical text, such as patient demographics, diagnoses, medications, and treatment plans. It uses a combination of machine learning algorithms and hand-crafted rules to analyze and interpret the text.

The goal of cTAKES is to help healthcare providers and researchers better understand and analyze large volumes of clinical data, and to support decision-making and research efforts. It can be used to support tasks such as population health management, quality improvement, and clinical research.

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:

Towards of automatically detecting brain death patterns through text mining
A Silva, F Portela, MF Santos… – 2016 IEEE 18th …, 2016 – ieeexplore.ieee.org
… So far, the NLP is used in automatic translation machines, dialogue systems, machine learning, intelligent computers, multimedia computers, expert … sign out” notes, pathology reports, ECG reports, and echocardiography reports [4]. Another well-known system is the cTAKES …

A common type system for clinical natural language processing
ST Wu, VC Kaggal, D Dligach, JJ Masanz… – Journal of biomedical …, 2013 – Springer
… Our description is consistent with the implementation in cTAKES v2.5 (http://sourceforge.net/ projects/ohnlp/files/cTAKES/) … embeds a deep semantic representation analogous to those that have been used in the computational semantics and dialogue systems communities [8, 9 …

Negbert: A transfer learning approach for negation detection and scope resolution
A Khandelwal, S Sawant – arXiv preprint arXiv:1911.04211, 2019 – arxiv.org
… from Sentiment Analysis, where the sentiment of a given sentence is dependent on negation, to query response systems like Chatbots, where negation … (2012) looked to improve Mayo Clinic’s clinical Text Analysis and Knowledge Extraction System (cTAKES) negation annotator …

Generality and reuse in a common type system for clinical natural language processing
ST Wu, VC Kaggal, GK Savova, H Liu, J Zheng… – Proceedings of the first …, 2011 – dl.acm.org
… that have been used in the computational semantics and dialogue systems communities[2 … J., Gawron, JM, Bratt, EO and Moore, R. The CommandTalk spoken dialogue system … CG Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component …

Machine Learning in Healthcare Communication
S Siddique, JCL Chow – Encyclopedia, 2021 – mdpi.com
… A pipeline was constructed using the clinical NLP system, UMLS, cTAKES, Metathesaurus, Seman … Traditional chatbots lack the capability to have conversations with respect to the … The research in human–computer interaction on the chatbot dialogue system equipped with an au …

A Machine Learning Technique for Reducing Hospital Readmissions for Diabetic Diseases
M Ismail, DPK Reddy, KS Srikanth – researchgate.net
… cTAKES separates essential NLP data from records and adds it to the data in CAS … Technology “ Volume 7 issue 3 1504-1507 July 2018 8. Mohammad Ismail K.Naga Lakshmi, Y. Kishore Reddy, M. Kireeti, T.Swathi” Design and Implementation of Student Chat Bot using AIML …

A Data-Centric Framework for Composable NLP Workflows
Z Liu, G Ding, A Bukkittu, M Gupta, P Gao… – arXiv preprint arXiv …, 2021 – arxiv.org
… porate independently-developed plugins, such as a plugin for answering multiple-choice questions, or a dialogue interface for chat-bots … 3.2 A ChatBot Workflow … such as DKPro (Eckart de Castilho and Gurevych, 2014), ClearTK (Bethard et al., 2014) and cTakes (Khalifa and …

Using Character-Level and Entity-Level Representations to Enhance Bidirectional Encoder Representation From Transformers-Based Clinical Semantic …
Y Xiong, S Chen, Q Chen, J Yan… – JMIR Medical …, 2020 – medinform.jmir.org
… These shared tasks mainly focus on general domains, including newswire, tutorial dialog system, Wikipedia, among others … We first deploy cTAKES [42], a popular clinical NLP tool, to extract entity mentions from text snippets, and then propose 2 methods to obtain the entity-level …

Big Data, Healthcare and IoT
PN Mahalle, SS Sonawane – … of Data Science Based Healthcare Internet …, 2021 – Springer
… 5. Social Media Data: There is rapid growth in social media resources such as Websites, blogs/microblog, chatbots, discussion forums … b. Apache cTAKES (clinical Text Analysis and Knowledge Extraction System) (https://ctakes.apache.org/) is an open source system specifically …

Usability and User eXperience Evaluation of Conversational Systems: A Systematic Mapping Study
GC Guerino, NMC Valentim – … of the 34th Brazilian Symposium on …, 2020 – dl.acm.org
… field. Ren et al. [47] carried out an SMS to characterize Usability eva- luation technologies used in chatbots. Results showed that chatbot Usability is a field under development, with very informal experi- mental studies. Despite …

Artificial Intelligence in Medicine: Chances and Challenges for Wide Clinical Adoption
J Varghese – Visceral medicine, 2020 – karger.com
… J Am Med Inform Assoc. 2018 May 1;25(5):593–602. External Resources: Crossref (DOI). Nadarzynski T, Miles O, Cowie A, Ridge D. Acceptability of artificial intelligence (AI)-led chatbot services in healthcare: A mixed-methods study. Digit Health …

Automatic disease annotation from radiology reports using artificial intelligence implemented by a recurrent neural network
C Lee, Y Kim, YS Kim, J Jang – American Journal of …, 2019 – Am Roentgen Ray Soc
… the Medical Language Extraction and Encoding System (MedLEE) [8] and Clinical Text Analysis and Knowledge Extraction system (cTAKES, version 2.0 … We used a sequence-to-sequence model, which is a sequence learning model used for chatbot, translation, and image …

Towards an OWL-based framework for extracting information from clinical texts
N Blaylock, W de Beaumont, J Allen… – Proceedings of the 2nd …, 2011 – dl.acm.org
… special issue on Best Practices in Spoken Language Dialogue Systems Engineering, 6(3):1–16 … Linking semantic and knowledge representations in a multi-domain dialogue system … Mayo clinical text analysis and knowledge extraction system (cTAKES): architecture, component …

CliCR: a dataset of clinical case reports for machine reading comprehension
S Šuster, W Daelemans – arXiv preprint arXiv:1803.09720, 2018 – arxiv.org
… We removed the HTML boilerplate from the crawled reports us- ing jusText3, segmented and tokenized the texts with cTakes (Savova et al., 2010), and annotated the medical … This and other embed- ding metrics for evaluation were previously studied in dialog-system research (

Clinical natural language processing for radiation oncology: A review and practical primer
DS Bitterman, TA Miller, RH Mak, GK Savova – International Journal of …, 2021 – Elsevier
… clinical Journal Pre-proof Page 22. 20 Text Analysis Knowledge Extraction System (cTAKES), 12,109 was recently assessed for its ability to extract toxicity data from a single institution’s unstructured radiotherapy on-treatment visit …

From medical records to research papers: a literature analysis pipeline for supporting medical genomic diagnosis processes
FL Bello, H Naya, V Raggio, A Rosá – Informatics in Medicine Unlocked, 2019 – Elsevier
… 18,19]. In addition to those methods, others (eg, Chikka et al. [20]) achieved a notable performance in information extraction, making use of specifically trained text mining models (eg, using Apache cTAKES [21]). Wu et al. [22 …

Synthnotes: Towards Synthetic Clinical Text Generation
KA Brown – 2019 – trace.tennessee.edu
… BLEU Bilingual Evaluation Understudy Score cTAKES clinical Text Analysis and Knowledge Extraction System CID Cluster Identifier … Among the most famous examples is the ELIZA [5] chatbot developed at the MIT Artificial Intelligence lab in the 1960’s. Using only the 2 Page 13 …

Combining contextualized embeddings and prior knowledge for clinical named entity recognition: Evaluation study
M Jiang, T Sanger, X Liu – JMIR medical informatics, 2019 – medinform.jmir.org
… In the early stage, most NER systems leverage rules and dictionaries to represent linguistic features and domain knowledge to identify clinical entities, such as MedLEE [1], SymText/MPlus [2,3], MetaMap [4], KnowledgeMap [5], cTAKES [6], and HiTEX [7]. To promote the …

Text Mining of Web-based Medical Content
J Bellika, A Bravo-Salgado, M Brezovan, DD Burdescu… – 2014 – books.google.com
… and the visually impaired 175 Olufemi Oyelami 7 An empirical study of user satisfaction with a health dialogue system designed for the Nigerian low-literate, computer-illiterate, and visually impaired 177 7.1 Introduction 177 7.2 Related work 178 7.3 Dialogue systems 181 7.4 …

Informatics in Medicine Unlocked
FL Bello, H Naya, V Raggio, A Rosá – researchgate.net
… 2 Page 3. [18,19]. In addition to those methods, others (eg, Chikka et al. [20]) achieved a notable performance in information extraction, making use of specifically trained text mining models (eg, using Apache cTAKES [21]). Wu et al …

Natural Language Processing (NLP) Applications In Patient Care: A Systematic Analysis
Z Shen – QRBD, 2020 – faculty.utrgv.edu
… N% Not reported 5 12% In-house developed 9 22% Readily available 26 5 3 2 2 14 64% cTAKES Python GATE … For example, patient care providers can implement chatbots to automate some of their communications with their patients to improve their operational efficiency …

Incorporating clinical notes in an early sepsis prediction model to improve performance
S Siddique – 2020 – essay.utwente.nl
… BOW bag-of-words cTAKES clinical Text Analysis and Knowledge Extraction System GBM Gradient Boosting Machine … of the disease from clinical text, generate “domain-aware automatic chest X-ray ra- diology reports”, or query a medical chatbot (12, 19, 26) …

Generation and mining of medical, case-based multiple choice questions
G Kurdi – 2020 – research.manchester.ac.uk
Page 1. GENERATION AND MINING OF MEDICAL, CASE-BASED MULTIPLE CHOICE QUESTIONS A THESIS SUBMITTED TO THE UNIVERSITY OF MANCHESTER FOR THE DEGREE OF DOCTOR OF PHILOSOPHY IN THE FACULTY OF SCIENCE AND ENGINEERING …

Data science in healthcare: benefits, challenges and opportunities
Z Abedjan, N Boujemaa, S Campbell, P Casla… – Data science for …, 2019 – Springer
… to interact with the general population directly, eg via crowdsourcing, analysing search logs (http://blogs.microsoft.com/next/ 2016/06/07/how-web-search-data-might-help-diagnose-serious- illness-earlier/# sm.0001mr81jwowvcp6zs81tmj7zmo81) or AI-based chatbots, are ways …

Towards an automated soap note: Classifying utterances from medical conversations
B Schloss, S Konam – Machine Learning for Healthcare …, 2020 – proceedings.mlr.press
Page 1. Proceedings of Machine Learning Research 1–21, 2020 Towards an Automated SOAP Note: Classifying Utterances from Medical Conversations Benjamin Schloss bschloss@abridge. com Abridge AI, Inc. Pittsburgh, PA, USA Sandeep Konam san@abridge.com …

Combining Natural Language Processing and Statistical Text Mining: A Study of Specialized Versus Common Languages
J Jarman – 2011 – scholarcommons.usf.edu
… 117 B.1 Negation . . . . . 117 B.2 MetaMap/MMtx . . . . . 118 B.3 UIMA/cTAKES . . . . . 118 B.4 GATE . . . . . 119 …

Automatic Detection of Emotions and Distress in Textual Data
E Mohammadi – 2019 – spectrum.library.concordia.ca
Page 1. Automatic Detection of Emotions and Distress in Textual Data Elham Mohammadi A Thesis in The Department of Computer Science and Software Engineering Presented in Partial Fulfillment of the Requirements for the Degree of Master of Computer Science at …

Opinion Mining on Digital Media Data: Advancing State-of-the-art Methods with Deep Learning
W Quan – 2020 – search.proquest.com
… NLP enables computers to perform a wide range of natural language related tasks at all levels, ranging from parsing and part-of-speech (POS) tagging, to machine translation and dialogue systems … chine translation, question answering, dialogue systems …

Using Artificial Intelligence to Improve Healthcare Quality and Efficiency
W Wang – 2020 – drum.lib.umd.edu
Page 1. ABSTRACT Title of Document: USING ARTIFICIAL INTELLIGENCE TO IMPROVE HEALTHCARE QUALITY AND EFFICIENCY Weiguang Wang, Doctor of Philosophy, 2020 Directed By: Guodong (Gordon) Gao, Professor …

Foundations of Data Science Based Healthcare Internet of Things
PN Mahalle – Springer
Page 1. SPRINGER BRIEFS IN APPLIED SCIENCES AND TECHNOLOGY ? COMPUTATIONAL INTELLIGENCE Parikshit N. Mahalle Sheetal S. Sonawane Foundations of Data Science Based Healthcare Internet of Things Page 2. SpringerBriefs in Applied Sciences …

Health analytics
A Makhlysheva, A Budrionis… – … Center for E-health …, 2018 – ehealthresearch.no
Page 1. Makhlysheva A., Budrionis A., Chomutare T., Nordsletta AT, Bakkevoll PA, Henriksen T., Hurley JS, Bellika JG, Blixgård H., Godtliebsen F., Skrøvseth SO, Solvoll T., Linstad L. Health Analytics REPORT 04/2018 Page 2. Health Analytics Report number 04-2018 …

Information Extraction on Free-Text Sleep Narratives using Natural Language Processing
S Fotedar – research.tue.nl
Page 1. Eindhoven University of Technology MASTER Information Extraction on Free-Text Sleep Narratives using Natural Language Processing Fotedar, Sonali Award date: 2020 Link to publication Disclaimer This document …

Integrating extra knowledge into word embedding models for biomedical NLP tasks
Y Ling, Y An, M Liu, SA Hasan, Y Fan… – 2017 International Joint …, 2017 – ieeexplore.ieee.org
Page 1. Integrating Extra Knowledge into Word Embedding Models for Biomedical NLP Tasks Yuan Ling ?† , Yuan An ? , Mengwen Liu ? , Sadid A. Hasan † , Yetian Fan ‡ and Xiaohua Hu ? ? College of Computing & Informatics …

Learning Clinical Data Representations for Machine Learning
LM Sulieman – 2018 – ir.vanderbilt.edu
… A representation that incorporates context and mimics the human way of comprehending text could improve the performance of NLP algorithms to answer questions in chat bots, identify sentiments in movie reviews, or classify the phenotypes in clinical notes …

Apache Solr
D Shahi – 2016 – 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 …

A bootstrapping approach with CRF and deep learning models for improving the biomedical named entity recognition in multi-domains
J Kim, Y Ko, J Seo – IEEE access, 2019 – ieeexplore.ieee.org
Page 1. 2169-3536 (c) 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org …

Improving Low-Resource Named-Entity Recognition and Neural Machine Translation
I Jauregi Unanue – 2020 – opus.lib.uts.edu.au
… tion detection [Mihalcea and Strapparava, 2009], machine translation [Koehn et al., 2003; Bahdanau et al., 2015], text summarization [Barzilay and Elhadad, 1999], poetry gener- ation [Zhang and Lapata, 2014] and dialogue systems [Weizenbaum, 1966; Gao et al …

Machine learning and electronic health records
S Stavland – 2020 – bora.uib.no
Page 1. Machine learning and electronic health records Sivert Stavland Master’s thesis in Software Engineering at Department of Computing, Mathematics and Physics, Bergen University College Department of Informatics, University of Bergen June 2020 Page 2. Page 3 …

A Computer-mediated Support for Writing Medical Notes with Coder’s Perspective
H Lukman – 2020 – repository.kulib.kyoto-u.ac.jp
Page 1. Title A Computer-mediated Support for Writing Medical Notes with Coder’s Perspective( Dissertation_?? ) Author(s) Lukman, Heryawan Citation Kyoto University (????) Issue Date 2020-09-23 URL https://doi.org/10.14989/doctor.k22804 Right …

An analysis of full-size Russian complexly NER labelled corpus of Internet user reviews on the drugs based on deep learning and language neuron nets
AG Sboeva, SG Sboevac, IA Moloshnikova… – sagteam.ru
Page 1. An analysis of full-size Russian complexly NER labelled corpus of Internet user reviews on the drugs based on deep learning and language neuron nets AG Sboeva,b,, SG Sboevac, IA Moloshnikova, AV Gryaznova, RB …