Towards the Applied Hybrid Model in Decision Making: Support the Early Diagnosis of Type 2 Diabetes (original) (raw)
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International Journal of Computational Intelligence Systems, 2011
A hybrid model, combining influence diagrams and a multicriteria method, is presented in order to assist with the decision making process about which questions would be more attractive to the definition of the diagnosis of Alzheimer's disease, considering the stages of Clinical Dementia Rating. The modeling and evaluation processes were carried out through a battery of standardized assessments for the evaluation of cases with Alzheimer's disease developed by Consortium to Establish a Registry for Alzheimer's disease.
Lecture Notes in Computer Science, 2009
This work presents a hybrid model, combining Influence Diagrams and the Multicriteria Method, for aiding to discover, from a battery of tests, which are the most attractive questions, in relation to the stages of Clinical Dementia Rating in decision making for the diagnosis of Alzheimer's disease. This disease is the most common dementia. Because of this and due to limitations in treatment at late stages of the disease early diagnosis is fundamental because it improves quality of life for patients and their families. Influence Diagram is implemented using GeNie tool. Next, the judgment matrixes are constructed to obtain cardinal value scales which are implemented through MACBETH Multicriteria Methodology. The modeling and evaluation processes were carried out through a battery of standardized assessments for the evaluation of cases with Alzheimer's disease developed by Consortium to Establish a Registry for Alzheimer's disease (CERAD).
Towards the Neuropsychological Diagnosis of Alzheimer’s Disease: A Hybrid Model in Decision Making
Communications in Computer and Information Science, 2009
Dementias are syndromes described by a decline in memory and other neuropsychological changes especially occurring in the elderly and increasing exponentially in function of age. Due to this fact and the therapeutical limitations in the most advanced stage of the disease, diagnosis of Alzheimer's disease is extremely important and it can provide better life conditions to patients and their families. This work presents a hybrid model, combining Influence Diagrams and the Multicriteria Method, for aiding to discover, from a battery of tests, which are the most attractive questions, in relation to the stages of CDR (Clinical Dementia Rating) in decision making for the diagnosis of Alzheimer's disease. This disease is the most common dementia. Influence Diagram is implemented using GeNie tool. Next, the judgment matrixes are constructed to obtain cardinal value scales which are implemented through MACBETH Multicriteria Methodology. The modeling and evaluation processes were carried out through a battery of standardized assessments for the evaluation of cases with Alzheimer's disease developed by Consortium to Establish a Registry for Alzheimer's disease (CERAD).
Lecture Notes in Computer Science, 2008
This work presents a hybrid model, combining Bayesian Networks and the Multicriteria Method, for aiding in decision making for the neuropsychological diagnosis of Alzheimer's disease. Due to the increase in life expectancy there is higher incidence of dementias. Alzheimer's disease is the most common dementia (alone or together with other dementias), accounting for 50% of the cases. Because of this and due to limitations in treatment at late stages of the disease early neuropsychological diagnosis is fundamental because it improves quality of life for patients and theirs families. Bayesian Networks are implemented using NETICA tool. Next, the judgment matrixes are constructed to obtain cardinal value scales which are implemented through MACBETH Multicriteria Methodology. The modeling and evaluation processes were carried out with the aid of a health specialist, bibliographic data and through of neuropsychological battery of standardized assessments.
A Multicriteria Model Applied in the Diagnosis of Alzheimer’s Disease
Lecture Notes in Computer Science, 2008
This study considers the construction of a multicriteria model to assist in the diagnosis of Alzheimer's disease. Alzheimer's disease is considered the most frequent of the dementias and it is responsible for about 50% of the cases. Due to this fact and the therapeutical limitations in the most advanced stage of the disease, diagnosis of Alzheimer's disease is extremely important and it can provide better life conditions to patients and their families. The main focus of this work is to develop a multicriteria model for aiding in decision making for the diagnosis of Alzheimer's disease, using Bayesian networks as a modeling tool. In this work, the modeling and evaluation processes have been conducted with the aid of a medical expert, bibliographic sources and battery of standardized assessments. The construction of cardinal value scales was implemented through Hiview and Macbeth.
Applying a Decision Making Model in the Early Diagnosis of Alzheimer’s Disease
Lecture Notes in Computer Science, 2007
This study considers the construction of a multicriteria model to assist in the early diagnosis of Alzheimer's disease. Alzheimer's disease is considered the most frequent of the dementias and it is responsible for about 50% of the cases. Due to this fact and the therapeutical limitations in the most advanced stage of the disease, early diagnosis of Alzheimer's disease is extremely important and it can provide better life conditions to patients and their families.
2009 IEEE International Conference on Intelligent Computing and Intelligent Systems, 2009
The Alzheimer's disease has become the most frequent cause of dementia in the last few years, and it is responsible, alone or in association with other diseases, for 50% of the cases in western countries. The main focus of this work is to develop a multicriteria model for aiding in decision making on the diagnosis of Alzheimer's disease by using the Aranau Tool, structured on the Verbal Decision Analysis. In this work, the modeling and evaluation processes were conducted with the aid of a medical expert, bibliographic sources and questionnaires. The questionnaires taken into account were based mainly on patients' neuroimaging tests, and we analyzed wheter or not there were problems in the patients' brain that could be relevant to the diagnosis of Alzheimer's disease.
2010
The Verbal Decision Analysis framework involves two ordering methods: PACOM and ZAPROS, being each method best suited for a determined context. The PA-COM method is indicated to problems having a small set of alternatives, being possible to solve models presenting many criteria. The ZAPROS method, though, should be applied to problems having a small criteria set, but presenting a great set of alternatives. Our proposal is to analyse both methods considering their advantages and disadvantages. An approach structured on the ZAPROS method but with some modifications to improve the alternatives comparison process will be also considered. A multicriteria model aiming at establishing which test from a determined set would be more likely to lead to the diagnosis of the Alzheimer's disease faster will be applied on the analysis. The model was previously structured and studied, and the results obtained by the application of each method will be exposed and discussed.
A Multicriteria Model Applied in the Diagnosis of Alzheimer's Disease: A Bayesian Network
2008 11th IEEE International Conference on Computational Science and Engineering, 2008
{p I ac í d o, c a I iop e} @un ifo r. br, akc as tr o @gm a i l. c o m Abstract This study considers the construction of a multicriteria model to assist in the diagnosis of Alzheimer's disease. Alzheimer's disease is considered the most frequent of the dementiqs and it is responsible for abouÍ 50% of the cases. Due to this fact and the íherapeutical limitations in the most advanced stage of Íhe disease, diagnosis of Alzheimer's disease ,s exÍremely imporíant and it can provide betÍer life conditions to patients and their families. The main focus of this work is to develop a multicriteria model for aiding in decísion making for the diagnosis of Alzheimer's diseose, using Bayesian networl<s as a modeling tool. In this work, the modeling and evaluation processes ltave been conducted with the aid ofa medical expert, bibliographic sources and battery of standardized assessments. Tlte construction of cardinal value scales was implemented through Hiview and Macbeth.
Towards the early diagnosis of Alzheimer's disease: a multicriteria model structured on neuroimaging
International Journal of Social and Humanistic Computing, 2009
The Alzheimer's disease has become the most frequent cause of dementia in the last few years. Despite its high incidence, it is proved that the disease has already been present for decades when the diagnosis is made. One of the great challenges nowadays is to identify the disease on its earliest stages, because the earliest the dementia is diagnosed, the greater the chances of delaying its advance. Concerning this fact, our main proposal is the development a multicriteria model for aiding in the decision making on the diagnosis of the Alzheimer's disease. It will be made by means of the Aranau Tool, a decision support system based on ZAPROS method. The modelling and evaluation processes were conducted with the aid of a medical expert, bibliographic sources and questionnaires, which were based mainly on patients' neuroimaging tests and were tried under various aspects that are relevant to the diagnosis.