Ana Karoline Araújo de Castro

A Multicriteria Model Applied in the Diagnosis of Alzheimer's Disease: A Bayesian Network

This study considers the construction of a multicriteria model to assist in the diagnosis of Alzheimerpsilas disease. Alzheimerpsilas 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 Alzheimerpsilas 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 Alzheimerpsilas 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.

A Novel Multicriteria Model Applied to Cashew Chestnut Industrialization Process

The industrialization process of cashew chestnut involves a decision making based on subjective criteria. It must be analyzed by the production manager, representing the decision maker, always aiming the choice of alternatives that maximize the entire almond index at the end of the process. Currently, this choice is carried out by the historical data verification, or considering the tacit experience of the manager. Therefore, the decision maker tends to miss the choice of the best possible solution. Due to the problem nature and to the necessity of the presentation of a good solution, the ZAPROS method was applied to the process. In the case study, the ZAPROS method application result was the relative and absolute ordinance of the alternatives, according to the DM’s preferences. A case study was realized at the most critical part of the industrialization process of the cashew chestnut.

An Approach for the Neuropsychological Diagnosis of Alzheimer’s Disease: A Hybrid Model in Decision Making

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 Alzheimers 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 Alzheimers disease developed by Consortium to Establish a Registry for Alzheimers disease (CERAD).

Towards the Applied Hybrid Model in Decision Making: A Neuropsychological Diagnosis of Alzheimer's Disease Study Case

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 Alzheimers 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 Alzheimers disease developed by Consortium to Establish a Registry for Alzheimers disease.

Applying a decision making model in the early diagnosis of Alzheimer's disease

This study considers the construction of a multicriteria model to assist in the early diagnosis of Alzheimers disease. Alzheimers 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 Alzheimers disease is extremely important and it can provide better life conditions to patients and their families.

A Hybrid Model for Aiding in Decision Making for the Neuropsychological Diagnosis of Alzheimer's Disease

This work presents a hybrid model, combining Bayesian Networks and the Multicriteria Method, for aiding in decision making for the neuropsychological diagnosis of Alzheimers disease. Due to the increase in life expectancy there is higher incidence of dementias. Alzheimers 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

This study considers the construction of a multicriteria model to assist in the diagnosis of Alzheimerpsilas disease. Alzheimerpsilas 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 Alzheimerpsilas 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 Alzheimerpsilas 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.

Towards the Neuropsychological Diagnosis of Alzheimer’s Disease: A Hybrid Model in Decision Making

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).

Applied hybrid model in the neuropsychological diagnosis of the Alzheimer's disease: a decision making study case

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 to the therapeutical limitations in the most advanced stage of the disease, diagnosis of Alzheimers disease is extremely important and it can provide better life conditions to patients and their families. A hybrid model, combining influence diagrams and a multicriteria method, is presented in order to assist in the decision making about which questions would be more attractive to the definition of the diagnosis of the Alzheimers disease, considering the stages of clinical dementia rating (CDR). The modelling and evaluation processes were carried out through a battery of standardised assessments for the evaluation of cases with Alzheimers disease developed by Consortium to Establish a Registry for Alzheimers disease (CERAD).

Applied Neuroimaging to the Diagnosis of Alzheimer’s Disease: A Multicriteria Model

In the last few years, Alzheimer’s disease has been the most frequent cause of dementia and it is responsible, alone or in association with other diseases, for 50% of the cases in western countries. Dementias are syndromes characterized by a decline in memory and other neuropsychological changes, especially occurring in elderly people and increasing exponentially along the aging process. 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.