Special Issue "Selected Papers from the Workshop on Intelligent Systems and Applications in Healthcare (ISA’Health 2016)"

A special issue of Information (ISSN 2078-2489).

Deadline for manuscript submissions: closed (31 October 2016)

Special Issue Editors

Guest Editor
Prof. José Manuel Ferreira Machado

Computer Science and Technology, ALGORITMI Research Centre, University of Minho, Portugal
Website | E-Mail
Interests: biomedical informatics; electronic health records; interoperability; databases; business intelligence; applied artificial intelligence
Guest Editor
Prof. António Carlos Silva Abelha

Computer Science and Technology, ALGORITMI RESEARCH Centre, University of Minho, Portugal
Website | E-Mail
Interests: electronic health records; interoperability; databases; applied artificial intelligence
Guest Editor
Prof. Manuel Filipe Vieira Torres dos Santos

Information Systems and Technologies, ALGORITMI RESEARCH Centre, University of Minho, Portugal
Website | E-Mail
Interests: artificial intelligence; business intelligence; data mining; intelligent data systems
Guest Editor
Prof. Carlos Filipe da Silva Portela

Information Systems and Technologies, ALGORITMI Research Centre, University of Minho; ESMAD, Polytechnic Institute of Oporto, Portugal
Website | E-Mail
Interests: data science; pervasive information system; artificial intelligence; decision support systems; data mining; business intelligence; biomedical informatics

Special Issue Information

Dear Colleagues,

The main business goal in healthcare is to increase the quality of services in healthcare while reducing costs. This objective contributes to improving the quality of life of patients, and, in some cases, reducing mortality and morbidity. To achieve this goal, the use of intelligent systems in the decision process becomes essential. The Workshop on Intelligent Systems and Applications in Healthcare (ISA’Health 2016) is focused on demonstrating how to take advantages of using Computer Intelligence, ensuring interoperability and security, overcoming local and temporal barriers in order to support the needs of society, and the development of innovative systems and applications to support healthcare decision support (http://idsist.wix.com/isahealth).

This workshop will bring together researchers who are working in the area of Intelligent System and Business Informatics. The cross-domain integration and appraisal of different fields, related to Intelligent Systems and Applications, provides an atmosphere to foster a variety of perspectives and opinions.

The main goal of this Special Issue is to extend the best workshop papers, presenting innovative and exciting works and promoting a discussion about how Intelligent Systems can contribute to improve the quality of the decision process in healthcare.

Prof. José Machado
Prof. António Abelha
Prof. Manuel Filipe Santos
Prof. Carlos Filipe Portela
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 350 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

 

Keywords

  • Intelligent Systems
  • Biomedical Engineering
  • Data Engineering
  • Applications
  • Artificial Intelligence
  • Information Systems
  • Intelligent Decision Support
  • Health Care

Published Papers (3 papers)

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Research

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Open AccessArticle Automated Detection of Liver Histopathological Findings Based on Biopsy Image Processing
Information 2017, 8(1), 36; doi:10.3390/info8010036
Received: 31 October 2016 / Revised: 5 March 2017 / Accepted: 14 March 2017 / Published: 20 March 2017
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Abstract
Hepatic steatosis is the accumulation of fat in the hepatic cells and the liver. Triglycerides and other kinds of molecules are included in the lipids. When there is some defect in the process, hepatic steatosis arise, during which the free fatty acids are
[...] Read more.
Hepatic steatosis is the accumulation of fat in the hepatic cells and the liver. Triglycerides and other kinds of molecules are included in the lipids. When there is some defect in the process, hepatic steatosis arise, during which the free fatty acids are taken by the liver and exuded as lipoproteins. Alcohol is the main cause of steatosis when excessive amounts are consumed for a long period of time. In many cases, steatosis can lead to inflammation that is mentioned as steatohepatitis or non-alcoholic steatohepatitis (NASH), which can later lead to fibrosis and finally cirrhosis. For automated detection and quantification of hepatic steatosis, a novel two-stage methodology is developed in this study. Initially, the image is processed in order to become more suitable for the detection of fat regions and steatosis quantification. In the second stage, initial candidate image regions are detected, and then they are either validated or discarded based on a series of criteria. The methodology is based on liver biopsy image analysis, and has been tested using 40 liver biopsy images obtained from patients who suffer from hepatitis C. The obtained results indicate that the proposed methodology can accurately assess liver steatosis. Full article
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Open AccessArticle Patients’ Admissions in Intensive Care Units: A Clustering Overview
Information 2017, 8(1), 23; doi:10.3390/info8010023
Received: 20 November 2016 / Revised: 13 February 2017 / Accepted: 14 February 2017 / Published: 17 February 2017
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Abstract
Intensive care is a critical area of medicine having a multidisciplinary nature requiring all types of healthcare professionals. Given the critical environment of intensive care units (ICUs), the need to use information technologies, like decision support systems, to improve healthcare services and ICU
[...] Read more.
Intensive care is a critical area of medicine having a multidisciplinary nature requiring all types of healthcare professionals. Given the critical environment of intensive care units (ICUs), the need to use information technologies, like decision support systems, to improve healthcare services and ICU management is evident. It is proven that unplanned and prolonged admission to the ICU is not only prejudicial to a patient's health, but also such a situation implies a readjustment of ICU resources, including beds, doctors, nurses, financial resources, among others. By discovering the common characteristics of the admitted patients, it is possible to improve these outcomes. In this study clustering techniques were applied to data collected from admitted patients in an intensive care unit. The best results presented a silhouette of 1, with a distance to centroids of 6.2 × 10−17 and a Davies–Bouldin index of −0.652. Full article
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Review

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Open AccessReview A Benchmarking Analysis of Open-Source Business Intelligence Tools in Healthcare Environments
Information 2016, 7(4), 57; doi:10.3390/info7040057
Received: 21 July 2016 / Revised: 8 October 2016 / Accepted: 10 October 2016 / Published: 13 October 2016
Cited by 1 | PDF Full-text (1019 KB) | HTML Full-text | XML Full-text
Abstract
In recent years, a wide range of Business Intelligence (BI) technologies have been applied to different areas in order to support the decision-making process. BI enables the extraction of knowledge from the data stored. The healthcare industry is no exception, and so BI
[...] Read more.
In recent years, a wide range of Business Intelligence (BI) technologies have been applied to different areas in order to support the decision-making process. BI enables the extraction of knowledge from the data stored. The healthcare industry is no exception, and so BI applications have been under investigation across multiple units of different institutions. Thus, in this article, we intend to analyze some open-source/free BI tools on the market and their applicability in the clinical sphere, taking into consideration the general characteristics of the clinical environment. For this purpose, six BI tools were selected, analyzed, and tested in a practical environment. Then, a comparison metric and a ranking were defined for the tested applications in order to choose the one that best applies to the extraction of useful knowledge and clinical data in a healthcare environment. Finally, a pervasive BI platform was developed using a real case in order to prove the tool viability. Full article
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