scholarly journals Fuzzy cognitive maps: a tool to improve diagnostic decisions

Diagnosis ◽  
2014 ◽  
Vol 1 (4) ◽  
pp. 289-293 ◽  
Author(s):  
Claudio Lucchiari ◽  
Raffaella Folgieri ◽  
Gabriella Pravettoni

AbstractAnticipating that the problem of diagnostic errors will not easily be solved through education, debiasing techniques or incentives-based systems, experts have proposed the systematic use of decision support tools (or decision aids) in medical practice. These tools are active knowledge resources that use patient data to generate case-specific advice to support clinical decision making. We argue that designing these decision support tools incorporates both discrete, analytical information as well as intuitive elements that would optimize their impact on clinical everyday activities. The use of fuzzy cognitive maps should allow developers to achieve this aim, by incorporating published evidence, intuition and qualitative assessment in a low-cost software program that could be implemented in various clinical settings.

Author(s):  
Márcio Mendonça ◽  
Guilherme Bender Sartori ◽  
Lucas Botoni de Souza ◽  
Giovanni Bruno Marquini Ribeiro

2020 ◽  
pp. 323
Author(s):  
Nour Elislam Djedaa ◽  
Abderrezak Moulay Lakhdar

2007 ◽  
Vol 7 (5-6) ◽  
pp. 53-60
Author(s):  
D. Inman ◽  
D. Simidchiev ◽  
P. Jeffrey

This paper examines the use of influence diagrams (IDs) in water demand management (WDM) strategy planning with the specific objective of exploring how IDs can be used in developing computer-based decision support tools (DSTs) to complement and support existing WDM decision processes. We report the results of an expert consultation carried out in collaboration with water industry specialists in Sofia, Bulgaria. The elicited information is presented as influence diagrams and the discussion looks at their usefulness in WDM strategy design and the specification of suitable modelling techniques. The paper concludes that IDs themselves are useful in developing model structures for use in evidence-based reasoning models such as Bayesian Networks, and this is in keeping with the objectives set out in the introduction of integrating DSTs into existing decision processes. The paper will be of interest to modellers, decision-makers and scientists involved in designing tools to support resource conservation strategy implementation.


2021 ◽  
Vol 167 ◽  
pp. 112313
Author(s):  
Zhaoyang Yang ◽  
Zhi Chen ◽  
Kenneth Lee ◽  
Edward Owens ◽  
Michel C. Boufadel ◽  
...  

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