scholarly journals Unsupervised Medical Entity Recognition and Linking in Chinese Online Medical Text

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Jing Xu ◽  
Liang Gan ◽  
Mian Cheng ◽  
Quanyuan Wu
Keyword(s):  
Decision Support ◽  
Medical Knowledge ◽  
Great Difficulty ◽  
Entity Recognition ◽  
Free Text ◽  
Data Annotation ◽  
Medical Text ◽  
Knowledge Based ◽  
Medical Entity ◽  
Unstructured Information

Online medical text is full of references to medical entities (MEs), which are valuable in many applications, including medical knowledge-based (KB) construction, decision support systems, and the treatment of diseases. However, the diverse and ambiguous nature of the surface forms gives rise to a great difficulty for ME identification. Many existing solutions have focused on supervised approaches, which are often task-dependent. In other words, applying them to different kinds of corpora or identifying new entity categories requires major effort in data annotation and feature definition. In this paper, we propose unMERL, an unsupervised framework for recognizing and linking medical entities mentioned in Chinese online medical text. For ME recognition, unMERL first exploits a knowledge-driven approach to extract candidate entities from free text. Then, the categories of the candidate entities are determined using a distributed semantic-based approach. For ME linking, we propose a collaborative inference approach which takes full advantage of heterogenous entity knowledge and unstructured information in KB. Experimental results on real corpora demonstrate significant benefits compared to recent approaches with respect to both ME recognition and linking.

scholarly journals MASK: A Success Story for An International Collaboration

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Mahmoud Azimaee ◽  
Gangamma Kalappa ◽  
Nikola Milosevic ◽  
Goran Nenadic ◽  
Hesam Dadafarin ◽  
...  
Keyword(s):  
Personal Information ◽  
Name Entity Recognition ◽  
Entity Recognition ◽  
Free Text ◽  
Rule Based ◽  
Data Annotation ◽  
Name Entity ◽  
Laboratory Test Results ◽  
Computer Scientists ◽  
The University

IntroductionA significant amount of valuable information in Electronic Health Records (EHR) such as laboratory test results or echocardiogram interpretations is embedded in lengthy free-text fields. Often patients’ personal information is also included in these narratives. Privacy legislation in different jurisdictions requires de-identification of this information prior to making it available for research. This process can be challenging and time-consuming. In particular, rule-based algorithms may lead to over-masking of essential medical terms, conditions, or devices that are named after individuals. Objectives and ApproachWe aimed to enhance ICES’ existing rule-based application to make it contextually-driven by applying Artificial Intelligence (AI). The ICES team collaborated with computer scientists at the University of Manchester who had already published work in this area and Evenset, a Toronto-based software company. Based on the Manchester University de-identification framework for name entity recognition, three machine learning-based algorithms for name entity recognition were implemented: CRF, BiLSTM recurrent neural networks with GLoVe and ELMo word embeddings. The models were trained on three different types of ICES data: Laboratory results, Electronic Medical Record (EMR) and echocardiogram data. Evenset developed the user interface and the masking modules. ResultsPreliminary tests have generated very promising results. To improve accuracy of the models, additional data annotation to expand the training datasets is currently being undertaken at ICES. The final framework will be available as an open-source tool for public. Conclusion / ImplicationsA collaborative approach for solving complex problems like de-identification of text-based medical data is highly efficient, especially where there are unique sets of expertise, resources, data and clinical knowledge among stakeholders.

scholarly journals An Unsupervised Approach to Structuring and Analyzing Repetitive Semantic Structures in Free Text of Electronic Medical Records

2021 ◽  
Author(s):  
Varvara Koshman ◽  
Anastasia Funkner ◽  
Sergey Kovalchuk
Keyword(s):  
Electronic Medical Records ◽  
Medical Records ◽  
Medical Data ◽  
Free Text ◽  
Automatic Annotation ◽  
Text Data ◽  
Data Annotation ◽  
Valuable Data ◽  
Medical Text ◽  
Unsupervised Approach

Electronic Medical Records (EMR) contain a lot of valuable data about patients, which is however unstructured. There is a lack of labeled medical text data in Russian and there are no tools for automatic annotation. We present an unsupervised approach to medical data annotation. Morphological and syntactical analyses of initial sentences produce syntactic trees, from which similar subtrees are then grouped by Word2Vec and labeled using dictionaries and Wikidata categories. This method can be used to automatically label EMRs in Russian and proposed methodology can be applied to other languages, which lack resources for automatic labeling and domain vocabularies.

An Intelligent Computer-Assisted Instruction System Designed for Rural Health Workers in Developing Countries

1992 ◽  
Vol 31 (03) ◽  
pp. 193-203 ◽  
Author(s):  
B. Auvert ◽  
V. Gilbos ◽  
F. Andrianiriana ◽  
W. E. Bertrand ◽  
X. Emmanuelli ◽  
...  
Keyword(s):  
Developing Countries ◽  
Decision Support ◽  
Rural Health ◽  
Health Workers ◽  
Computer Assisted Instruction ◽  
Computer Assisted ◽  
Instruction System ◽  
Knowledge Based ◽  
Assisted Instruction ◽  
Intelligent Computer

Abstract:This paper describes an intelligent computer-assisted instruction system that was designed for rural health workers in developing countries. This system, called Consult-EAO, includes an expert module and a coaching module. The expert module, which is derived from the knowledge-based decision support system Tropicaid, covers most of medical practice in developing countries. It allows for the creation of outpatient simulations without the help of a teacher. The student may practice his knowledge by solving problems with these simulations. The system gives some initial facts and controls the simulation during the session by guiding the student toward the most efficient decisions. All student answers are analyzed and, if necessary, criticized. The messages are adapted to the situation due to the pedagogical rules of the coaching module. This system runs on PC-compatible computer.

A Medical Text Analysis System for German - Syntax Analysis

1991 ◽  
Vol 30 (04) ◽  
pp. 275-283 ◽  
Author(s):  
P. M. Pietrzyk
Keyword(s):  
Text Analysis ◽  
Free Text ◽  
New Approach ◽  
Syntax Analysis ◽  
Medical Text ◽  
Medical Language ◽  
Computerized Processing ◽  
Language Data ◽  
Analysis System ◽  
German Syntax

Abstract:Much information about patients is stored in free text. Hence, the computerized processing of medical language data has been a well-known goal of medical informatics resulting in different paradigms. In Gottingen, a Medical Text Analysis System for German (abbr. MediTAS) has been under development for some time, trying to combine and to extend these paradigms. This article concentrates on the automated syntax analysis of German medical utterances. The investigated text material consists of 8,790 distinct utterances extracted from the summary sections of about 18,400 cytopathological findings reports. The parsing is based upon a new approach called Left-Associative Grammar (LAG) developed by Hausser. By extending considerably the LAG approach, most of the grammatical constructions occurring in the text material could be covered.

An Integrated Approach for a Knowledge-based Clinical Workstation: Architecture and Experience

1998 ◽  
Vol 37 (01) ◽  
pp. 16-25 ◽  
Author(s):  
P. Ringleb ◽  
T. Steiner ◽  
P. Knaup ◽  
W. Hacke ◽  
R. Haux ◽  
...  
Keyword(s):  
Decision Support ◽  
Information Systems ◽  
Patient Care ◽  
Hospital Information Systems ◽  
Medical Decision ◽  
Daily Routine ◽  
Functional Requirements ◽  
Support Functions ◽  
Knowledge Based ◽  
Clinical Workstation

Abstract:Today, the demand for medical decision support to improve the quality of patient care and to reduce costs in health services is generally recognized. Nevertheless, decision support is not yet established in daily routine within hospital information systems which often show a heterogeneous architecture but offer possibilities of interoperability. Currently, the integration of decision support functions into clinical workstations is the most promising way. Therefore, we first discuss aspects of integrating decision support into clinical workstations including clinical needs, integration of database and knowledge base, knowledge sharing and reuse and the role of standardized terminology. In addition, we draw up functional requirements to support the physician dealing with patient care, medical research and administrative tasks. As a consequence, we propose a general architecture of an integrated knowledge-based clinical workstation. Based on an example application we discuss our experiences concerning clinical applicability and relevance. We show that, although our approach promotes the integration of decision support into hospital information systems, the success of decision support depends above all on an adequate transformation of clinical needs.

IMPLEMENTASI METODE VIKOR DALAM PENERIMAAN JURNALIS PADA KORAN WASPADA MEDAN

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Soraya Rahma Hayati ◽  
Mesran Mesran ◽  
Taronisokhi Zebua ◽  
Heri Nurdiyanto ◽  
Khasanah Khasanah
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Decision Support Systems ◽  
Support System ◽  
Support Systems ◽  
Knowledge Based ◽  
Computer Based ◽  
Support Decision Making ◽  
Made In

The reception of journalists at the Waspada Daily Medan always went through several rigorous selections before being determined to be accepted as journalists at the Waspada Medan Daily. There are several criteria that must be possessed by each participant as a condition for becoming a journalist in the Daily Alert Medan. To get the best participants, the Waspada Medan Daily needed a decision support system. Decision Support Systems (SPK) are part of computer-based information systems (including knowledge-based systems (knowledge management)) that are used to support decision making within an organization or company. Decision support systems provide a semitructured decision, where no one knows exactly how the decision should be made. In this study the authors applied the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) as the method to be applied in the decision support system application. The VIKOR method is part of the Multi-Attibut Decision Making (MADM) Concept, which requires normalization in its calculations. The expected results in this study can obtain maximum decisions.Keywords: Journalist Acceptance, Decision Support System, VIKOR

Rancang Bangun Aplikasi Penjurusan Minat Bakat Menggunakan Metode Forward Chaining

2016 ◽  
Vol 7 (2) ◽  
pp. 155-160
Author(s):  
Levi Jordan Halim ◽  
Ranny Ranny ◽  
P.M. Winarno
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Multiple Intelligence ◽  
Student Activities ◽  
Forward Chaining ◽  
Knowledge Based ◽  
Activity Unit ◽  
Index Terms ◽  
Intelligence Scores

Plentiful choices of Student Activities Unit that offered by a campus like Multimedia Nusantara University can help students who want to choose a unit that suitable for them. The decision support system application with Forward Chaining method is built to help students choosing the Student Activity Unit that suits them. Multiple Intelligence method is used as the knowledge base at making the rules. The aspects that considered as attributes to choosing the Student Activities Unit is the initial interest and also the multiple intelligence scores that the level of conformity will be searched by using Forward Chaining method. This research has produced a knowledge-based decision support system that can help students at choosing Student Activities Unit that suitable for them with the highest accuracy of 86.67 percent. This system is designed in website with PHP and MySQL database programming language. Index Terms—Forward Chaining, Knowledge-based, Multimedia Nusantara University, Multiple Intelligence, Student Activities Unit 

Sign in / Sign up

Export Citation Format

Share Document