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Handbook of Research on ICTs and Management Systems for Improving Efficiency in Healthcare and Social Care
Is the group of records in a database that were selected according to the search that matches the goal that you want to reach (identify rheumatic diseases).
Published in Chapter:
Intelligent Agent to Identify Rheumatic Diseases
Gustavo Julio Puente Salcido (Universidad Autónoma de Coahuila, México) and Eduardo César Contreras Delgado (Universidad Autónoma de Coahuila, México)
DOI: 10.4018/978-1-4666-3990-4.ch023
Abstract
Most of Mexican populations, even medical population, do not have enough information on rheumatic diseases to allow them to understand the importance of the socioeconomic and psychological impact of these disorders. In order to reduce this problem, a didactic tool is provided to general practitioners that enables them to identify medical disorders in the area of rheumatology. Didactic software is based on the application of an intelligent agent based on goals that contains enough information to identify seven of the most common inflammatory rheumatic diseases and fourteen non-inflammatory. The purpose of this tool is that a general practitioner can get an early diagnosis in a rheumatic patient and subsequently send that patient to a rheumatologist in order to prevent damage. The presented prototype can be useful for professors and students of the computation area to solve similar problems.
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Intelligent Agent to Identify Rheumatic Diseases
Is the group of records in a database that were selected according to the search that matches the goal that you want to reach (identify rheumatic diseases).
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Evolutionary Approaches for ANNs Design
Set of all possible situations of the problem that we want to solve could ever be in.
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Nelder-Mead Evolutionary Hybrid Algorithms
Set of all possible solutions for any given optimization problem, in which one can usually define a neighborhood of any solution.
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Improving Energy Efficiency in Industry 4.0 With Multi-Objective Optimization
Set of all possible solutions for any given optimization problem. Almost always, a neighborhood around each solution can also be defined in the search space.
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Evolutionary Grammatical Inference
Set of all candidate solutions of a given problem instance.
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Genetic Algorithms in Multimodal Search Space
Set of all possible situations of the problem that want to be solved. Combination of all the possible values for all the variables involved with the problem.
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Differential Evolution with Self-Adaptation
Set of all possible situations of the optimization problem that we want to solve.
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Stationary Density of Stochastic Search Processes
This is the set of all the feasible solutions for an optimization problem.
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Search Space Reduction in Biometric Databases: A Review
The portion of the database to be searched ( i.e. , compared) to identify a query.
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2D-PAGE Analysis Using Evolutionary Computation
Set of all possible situations of the problem that we want to solve could ever be in.
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EA Multi-Model Selection for SVM
Set of all possible situations of the problem that we want to solve could ever be in.
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Evolving Graphs for ANN Development and Simplification
Set of all possible situations of the problem that we want to solve could ever be in.
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Finding Multiple Solutions with GA in Multimodal Problems
Set of all possible situations of the problem that we want to solve could ever be in. Combination of all the possible values for all the variables related with the problem.
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Template Matching in Digital Images with Swarm Intelligence
The set of all possible solutions to a determined problem. Generally, the search space is multi-dimensional, as the cost function.
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Multi-Objective Evolutionary Algorithms
Set of all possible solutions for any given optimization problem. Almost always, a neighborhood around each solution can also be defined in the search space
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Optimization of the Acoustic Systems
Set of all possible situations of the problem that we want to solve could ever be in.
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ANN Development with EC Tools: An Overview
Set of all possible situations of the problem that we want to solve could ever be in.
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Evolutionary Approaches to Variable Selection
Set of all possible situations of the problem that we want to solve could ever be in. Combination of all the possible values for all the variables related with the problem.
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