Integrated AHP-TOPSIS Method for the Assessment of Health Management Information Systems Efficiency

Hamid

Artificial Intelligence in Medicine

et al. 2021

Highlights Develop a new framework that can handle the prioritisation of patients with COVID-19 and can detect the health conditions of asymptomatic carriers. The most important laboratory criteria were selected and implemented based on two feature selection approaches (i.e. data-driven and knowledge-driven). A new decision matrix was developed based on a crossover of (i) multi-laboratory characteristics criteria and (ii) lists of infected patients for patient prioritisation using integration Entropy-TOPSIS methods. Advantages of new framework in detecting/recognising the health condition of patients prior to discharge, supporting the hospitalisation characteristics, managing patient care and optimising clinical prediction rule.

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Detection-based prioritisation: Framework of multi-laboratory characteristics for asymptomatic COVID-19 carriers based on integrated Entropy–TOPSIS methods

Hamid

Artificial Intelligence in Medicine

et al. 2021

5th International Thematic Monograph: Modern Management Tools and Economy of Tourism Sector in Present Era

“…TOPSIS method performs prioritization of alternatives based on their geometric distance from the positive-ideal and negative-ideal solution. Accordingly, it can be concluded that the best alternative will be the one with the shortest distance to the positive-ideal solution, and with the greatest distance from the negative-ideal solution (Rađenović & Veselinović, 2017). TOPSIS method involves the use of specific steps (Yoon & Hwang, 1995):…”

Section: Figure 1 Component Matrix Plotmentioning

confidence: 99%

European Travel and Tourism Ict Readiness: Pca/Swara Approach

Rađenović¹,

Niš²,

Marjanović³

2020

Self Cite

The development of information and communication technology has led to the transformation of traditional business practices in all sectors of the economy. Information and communication technologies in the field of tourism represent a generator of change and drivers of development, by enabling the creation and retention of a large number of jobs, business opportunities and significant added value. Given the well-recognized value of the information and communication technologies in tourism, this chapter sought to identify the countries with the highest level of travel and tourism ICT readiness. Therefore, a two-step analysis was applied where in the first step the weights were determined using two approaches, PCA and SWARA. In the second step, using multicriteria analysis, the evaluation of ICT readiness of European countries was performed. The results indicate that the application of weight coefficients determined by different approaches in the same multicriteria method leads to moderate rank inversion.

“…The Technique for Order Performance by Similarity to Ideal Solution (TOPSIS), first proposed by Hwang and Yoon in 1981, is an MCDM widely used, in the presence of multiple and usually conflicting criteria, to evaluate and rank the performance of alternatives with respect to multiple criteria by similarity with the ideal solution [38].…”

Section: Topsismentioning

confidence: 99%

“…The main procedure of TOPSIS based on the geometric distance method representing ''closeness to the ideal'' is described in the following steps [38]: STEP T1. Build the normalized new decision matrix Y = [y i,j ] N a ×N c .…”

Section: Topsismentioning

confidence: 99%

Building an Improved Internet of Things Smart Sensor Network Based on a Three-Phase Methodology

et al. 2019

In recent years, the Internet of Things (IoT) has allowed the easy, intelligent, and efficient connection of many devices used in daily life by means of numerous smart sensors which communicate with each other using wireless signals. The rapid development of the IoT has been a result of recent advances in sensing technology. This paper proposes a three-phase methodology to improve the quality of experience for IoT system technologies. The proposed method employs the concepts of simple routing and two well-known multi-criteria decision-making method (MCDM) techniques: The Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). First, all simple routings are obtained using the proposed depth-first search technology (DFS). AHP is applied to analyze the structure of the problem and to obtain weights for various selected criteria in the second phase. In the third phase, TOPSIS is utilized to rank the simple routings, which are simple paths. A case study example is provided to demonstrate the proposed three-phase methodology. The results from the numerical experiments show that the proposed methodology can successfully achieve the aim of this paper.