scholarly journals Fuzzy Cognitive Scenario Mapping for Causes of Cybersecurity in Telehealth Services

Healthcare ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1504
Author(s):  
Thiago Poleto ◽  
Victor Diogho Heuer de Carvalho ◽  
Ayara Letícia Bentes da Silva ◽  
Thárcylla Rebecca Negreiros Clemente ◽  
Maísa Mendonça Silva ◽  
...  
Keyword(s):  
Scenario Analysis ◽  
Medical Records ◽  
Expert Knowledge ◽  
Common Factors ◽  
State Level ◽  
Cognitive Maps ◽  
Fuzzy Cognitive Maps ◽  
Geographical Distance ◽  
Secure Systems ◽  
Confidential Data

Hospital organizations have adopted telehealth systems to expand their services to a portion of the Brazilian population with limited access to healthcare, mainly due to the geographical distance between their communities and hospitals. The importance and usage of those services have recently increased due to the COVID-19 state-level mobility interventions. These services work with sensitive and confidential data that contain medical records, medication prescriptions, and results of diagnostic processes. Understanding how cybersecurity impacts the development of telehealth strategies is crucial for creating secure systems for daily operations. In the application reported in this article, the Fuzzy Cognitive Maps (FCMs) translated the complexity of cybersecurity in telehealth services into intelligible and objective results in an expert-based cognitive map. The tool also allowed the construction of scenarios simulating the possible implications caused by common factors that affect telehealth systems. FCMs provide a better understanding of cybersecurity strategies using expert knowledge and scenario analysis, enabling the maturation of cybersecurity in telehealth services.

A Review of the Application of Fuzzy Cognitive Maps in the Policy Decision-Making Life Cycle

2014 ◽  
pp. 129-148
Author(s):  
Andreas S. Andreou ◽  
Haris Neophytou ◽  
Constantinos Stylianou
Keyword(s):  
Expert Knowledge ◽  
Policy Decision ◽  
Cognitive Maps ◽  
Fuzzy Cognitive Maps ◽  
Qualitative Modeling ◽  
Current State ◽  
Specific Factors ◽  
Policy Decision Making ◽  
State Of Affairs ◽  
The Impact

Fuzzy cognitive maps are a qualitative modeling technique that uses expert knowledge to attempt to represent the interactions between problem-specific factors aiming to simulate how these interactions alter the factors and drive the current state of a problem to a different state. Recent years have seen an increase in the number of research attempts that propose the adoption of Fuzzy cognitive maps (FCMs) as a means to forecast the effect of a policy in a number of interesting domains, including land use, urban (re)development, and other social, political, or economic issues or to simulate the current state of affairs to pinpoint possible hotspots for creating a policy. This chapter presents an overview of these research attempts where fuzzy cognitive maps have been employed as a simulation tool in order to support decision makers in their assessment of the impact of policies and help them adopt the most suitable policy to implement.

scholarly journals FCM Expert: Software Tool for Scenario Analysis and Pattern Classification Based on Fuzzy Cognitive Maps

2018 ◽  
Vol 27 (07) ◽  
pp. 1860010 ◽  
Author(s):  
Gonzalo Nápoles ◽  
Maikel Leon Espinosa ◽  
Isel Grau ◽  
Koen Vanhoof
Keyword(s):  
Pattern Classification ◽  
Scenario Analysis ◽  
Cognitive Modeling ◽  
Software Tool ◽  
Cognitive Maps ◽  
Machine Learning Algorithms ◽  
Fuzzy Cognitive Maps ◽  
Software Products ◽  
Knowledge Based ◽  
The Rich

Fuzzy Cognitive Maps (FCMs) have become a suitable and proven knowledge-based methodology for systems modeling and simulation. This technique is especially attractive when modeling systems characterized by ambiguity, and/or non-trivial causalities among its variables. The rich literature that is found related to FCMs reports very clearly many successful studies solved through the use of FCMs; however, when it comes to software implementations, where domain experts can design FCM-based systems, run simulations or perform more advanced experiments, not much is found or documented. The few existing implementations are not proficient in providing options for experimentation. Therefore, we believe that a gap exists, specifically between the theoretical advances and the development of accurate, transparent and sound FCM-based systems; and we advocate for the creation of more complete and exible software products. The goal of this paper is to introduce “FCM Expert”, a software tool for fuzzy cognitive modeling, where we focus on scenario analysis and pattern classification. The main features of FCM Expert rely on Machine Learning algorithms to compute the parameters that might define a model, optimize its network topology and improve the system convergence without losing information. Also, FCM Expert allows performing WHAT-IF simulations and studying the system behavior through a friendly, intuitive and easy-to-use graphical user interface.

FUZZY COGNITIVE MAPS EMBEDDED IN A LOW COST AUTONOMOUS MOBILE ROBOT

2019 ◽  
Author(s):  
Márcio Mendonça ◽  
Guilherme Bender Sartori ◽  
Lucas Botoni de Souza ◽  
Giovanni Bruno Marquini Ribeiro
Keyword(s):  
Mobile Robot ◽  
Low Cost ◽  
Cognitive Maps ◽  
Fuzzy Cognitive Maps ◽  
Autonomous Mobile Robot
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