scholarly journals Visual Exploration of Medical Records

2021 ◽  
Author(s):  
Ursula Torres Parejo ◽  
Jesús Roque Campaña ◽  
María Amparo Vila ◽  
Miguel Delgado
Keyword(s):  
Information Retrieval ◽  
Medical Records ◽  
Visual Exploration ◽  
Medical Field ◽  
Medical Databases ◽  
Tag Clouds ◽  
Tag Cloud ◽  
Content Representation ◽  
Content Identification ◽  
Visual Interface

Medical records contain many terms which are difficult to process. Our aim in this study is to allow the visual exploration of the information in medical databases where the texts presents a large number of syntactic variations and abbreviations, through an interface which facilitates content identification, navigation and information retrieval. We propose the use of multi-term tag clouds as content representation tools and as assistants for the browsing and querying tasks. The tag cloud generation is achieved through a novelty mathematical method that allows related terms to remain grouped together within the tags To evaluate this proposal, we have used a database with 24,481 records. 23 expert users in the medical field were tasked to complete a survey to evaluate the generated tag clouds properties and we obtained a precision of 0.990, a recall of 0.870 and a F1score of 0.904 in the evaluation of the tag cloud as an information retrieval tool. The main contribution of this approach is that we automatically generate a visual interface over the text capable of capturing the semantics of the information and facilitating access to medical records.

scholarly journals On Building and Evaluating a Medical Records Exploration Interface Using Text Mining Techniques

Entropy ◽  
2021 ◽  
Vol 23 (10) ◽  
pp. 1275
Author(s):  
Úrsula Torres Torres Parejo ◽  
Jesús Roque Campaña ◽  
María Amparo Vila ◽  
Miguel Delgado
Keyword(s):  
Information Retrieval ◽  
Medical Records ◽  
Visual Exploration ◽  
Medical Databases ◽  
Tag Clouds ◽  
Tag Cloud ◽  
Degree Of Satisfaction ◽  
Content Identification ◽  
High Degree ◽  
Visual Interface

Medical records contain many terms that are difficult to process. Our aim in this study is to allow visual exploration of the information in medical databases where texts present a large number of syntactic variations and abbreviations by using an interface that facilitates content identification, navigation, and information retrieval. We propose the use of multi-term tag clouds as content representation tools and as assistants for browsing and querying tasks. The tag cloud generation is achieved by using a novelty mathematical method that allows related terms to remain grouped together within the tags. To evaluate this proposal, we have carried out a survey over a spanish database with 24,481 records. For this purpose, 23 expert users in the medical field were tasked to test the interface and answer some questions in order to evaluate the generated tag clouds properties. In addition, we obtained a precision of 0.990, a recall of 0.870, and a F1-score of 0.904 in the evaluation of the tag cloud as an information retrieval tool. The main contribution of this approach is that we automatically generate a visual interface over the text capable of capturing the semantics of the information and facilitating access to medical records, obtaining a high degree of satisfaction in the evaluation survey.

A survey of tag clouds as tools for information retrieval and content representation

2020 ◽  
pp. 147387162096663
Author(s):  
Úrsula Torres Parejo ◽  
Jesús R Campaña ◽  
M Amparo Vila ◽  
Miguel Delgado
Keyword(s):  
Information Retrieval ◽  
Structural Properties ◽  
The Internet ◽  
Original Text ◽  
Semantic Association ◽  
Tag Clouds ◽  
Tag Cloud ◽  
Content Representation ◽  
Visual Interfaces

Tag clouds are tools that have been widely used on the Internet since their conception. The main applications of these textual visualizations are information retrieval, content representation and browsing of the original text from which the tags are generated. Despite the extensive use of tag clouds, their enormous popularity and the amount of research related to different aspects of them, few studies have summarized their most important features when they work as tools for information retrieval and content representation. In this paper we present a summary of the main characteristics of tag clouds found in the literature, such as their different functions, designs and negative aspects. We also present a summary of the most popular metrics used to capture the structural properties of a tag cloud generated from the query results, as well as other measures for evaluating the goodness of the tag cloud when it works as a tool for content representation. The different methods for tagging and the semantic association processes in tag clouds are also considered. Finally we give a list of alternative for visual interfaces, which makes this study a useful first help for researchers who want to study the content representation and information retrieval interfaces in greater depth.

Research on the Layout of the Chinese Tag Cloud

2013 ◽  
Vol 760-762 ◽  
pp. 2060-2063
Author(s):  
Yuan Zhang ◽  
Yun Lin
Keyword(s):  
Information Retrieval ◽  
Visual Features ◽  
Tag Clouds ◽  
Tag Cloud ◽  
Browsing Behavior

Tag clouds are now very popular in websites because of its ability to recruit the activity of web users into effectively information retrieval. In recent years, although there are many researches on English tag clouds, few are known about Chinese tag clouds. In this paper, we investigated the layout of the Chinese tag cloud, and analyzed eight visual features of the Chinese tag cloud according to users browsing behavior. Our results could provide a theoretical reference for the tag cloud designers.

CobWeb Multidimensional Model and Tag-Cloud Operators for OLAP of Documents

2018 ◽  
Vol 9 (2) ◽  
pp. 46-68
Author(s):  
Omar Khrouf ◽  
Kais Khrouf ◽  
Jamel Feki
Keyword(s):  
Decision Makers ◽  
Effective Management ◽  
Multidimensional Model ◽  
Tag Clouds ◽  
Xml Documents ◽  
Model Based ◽  
Tag Cloud ◽  
On Line ◽  
Analytical Processing ◽  
Software Prototype

There is an explosion in the amount of textual documents that have been generated and stored in recent years. Effective management of these documents is essential for better exploitation in decisional analyses. In this context, the authors propose their CobWeb multidimensional model based on standard facets and dedicated to the OLAP (on-line analytical processing) of XML documents; it aims to provide decision makers with facilities for expressing their analytical queries. Secondly, they suggest new visualization operators for OLAP query results by introducing the concept of Tag clouds as a means to help decision-makers to display OLAP results in an intuitive format and focus on main concepts. The authors have developed a software prototype called MQF (Multidimensional Query based on Facets) to support their proposals and then tested it on documents from the PubMed collection.

scholarly journals A Fog Computing-Based Architecture for Medical Records Management

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Cícero A. Silva ◽  
Gibeon S. Aquino ◽  
Sávio R. M. Melo ◽  
Dannylo J. B. Egídio
Keyword(s):  
Medical Records ◽  
Fog Computing ◽  
Medical Data ◽  
Data Sources ◽  
Medical Applications ◽  
Records Management ◽  
Medical Field ◽  
Computing Paradigm ◽  
And Storage

The aging of the world’s population and the growth in the number of people with chronic diseases have increased expenses with medical care. Thus, the use of technological solutions has been widely adopted in the medical field to improve the patients’ health. In this context, approaches based on Cloud Computing have been used to store and process the information generated in these solutions. However, using Cloud can create delays that are intolerable for medical applications. Thus, the Fog Computing paradigm emerged as an alternative to overcome this problem, bringing computation and storage closer to the data sources. However, managing medical data stored in Fog is still a challenge. Moreover, characteristics of availability, performance, interoperability, and privacy need to be considered in approaches that aim to explore this problem. So, this article shows a software architecture based on Fog Computing and designed to facilitate the management of medical records. This architecture uses Blockchain concepts to provide the necessary privacy features and to allow Fog Nodes to carry out the authorization process in a distributed way. Finally, this paper describes a case study that evaluates the performance, privacy, and interoperability requirements of the proposed architecture in a home-centered healthcare scenario.

Retrieving Medical Records Using Bayesian Networks

2011 ◽  
pp. 2274-2280
Author(s):  
Luis M. De Campos
Keyword(s):  
Information Retrieval ◽  
Bayesian Networks ◽  
Graphical Models ◽  
Medical Records ◽  
Network Models ◽  
Boolean Expression ◽  
Wide Range ◽  
Structured Information Retrieval ◽  
Structured Information ◽  
Bayesian Network Models

Bayesian networks (Jensen, 2001) are powerful tools for dealing with uncertainty. They have been successfully applied in a wide range of domains where this property is an important feature, as in the case of information retrieval (IR) (Turtle & Croft, 1991). This field (Baeza-Yates & Ribeiro- Neto, 1999) is concerned with the representation, storage, organization, and accessing of information items (the textual representation of any kind of object). Uncertainty is also present in this field, and, consequently, several approaches based on these probabilistic graphical models have been designed in an attempt to represent documents and their contents (expressed by means of indexed terms), and the relationships between them, so as to retrieve as many relevant documents as possible, given a query submitted by a user. Classic IR has evolved from flat documents (i.e., texts that do not have any kind of structure relating their contents) with all the indexing terms directly assigned to the document itself toward structured information retrieval (SIR) (Chiaramella, 2001), where the structure or the hierarchy of contents of a document is taken into account. For instance, a book can be divided into chapters, each chapter into sections, each section into paragraphs, and so on. Terms could be assigned to any of the parts where they occur. New standards, such as SGML or XML, have been developed to represent this type of document. Bayesian network models also have been extended to deal with this new kind of document. In this article, a structured information retrieval application in the domain of a pathological anatomy service is presented. All the medical records that this service stores are represented in XML, and our contribution involves retrieving records that are relevant for a given query that could be formulated by a Boolean expression on some fields, as well as using a text-free query on other different fields. The search engine that answers this second type of query is based on Bayesian networks.

Computer-Assisted Research of Medical Records

1970 ◽  
Vol 09 (03) ◽  
pp. 171-176
Author(s):  
L. J. Schneiderman ◽  
M. Baylor
Keyword(s):  
Information Retrieval ◽  
Physical Examination ◽  
Student Teaching ◽  
Medical Records ◽  
University Hospital ◽  
Computer Assisted ◽  
Free Text ◽  
Text Mode ◽  
Statistical Studies ◽  
Hospital Clinic

The Facilitated Access File, described herein, has proved to be an acceptable, relatively simple, yet feasible strategy for general medical record information retrieval at a university hospital clinic. Physicians record physical examination data in free-text mode, then through a rapid exercise of judgment, create an index to these data which is computer-stored. Such an index file provides future investigators facilitated access back to the original handwritten data and permits a variety of statistical studies. The system has been in use for over a year and has proved to be of value in clinical research and student teaching.

MTCIR: A multi-term tag cloud information retrieval system

2013 ◽  
Vol 40 (14) ◽  
pp. 5448-5455 ◽  
Author(s):  
Ursula Torres-Parejo ◽  
Jesús R. Campaña ◽  
Miguel Delgado ◽  
M. Amparo Vila
Keyword(s):  
Information Retrieval ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Tag Cloud
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