Brain activity and medical diagnosis: an EEG study.

BACKGROUND: Despite new brain imaging techniques that have improved the study of the underlying processes of human decision-making, to the best of our knowledge, there have been very few studies that have attempted to investigate brain activity during medical diagnostic processing. We investigated brain electroencephalography (EEG) activity associated with diagnostic decision-making in the realm of veterinary medicine using X-rays as a fundamental auxiliary test. EEG signals were analysed using Principal Components (PCA) and Logistic Regression Analysis RESULTS: The principal component analysis revealed three patterns that accounted for 85% of the total variance in the EEG activity recorded while veterinary doctors read a clinical history, examined an X-ray image pertinent to a medical case, and selected among alternative diagnostic hypotheses. Two of these patterns are proposed to be associated with visual processing and the executive control of the task. The other two patterns are proposed to be related to the reasoning process that occurs during diagnostic decision-making. CONCLUSIONS: PCA analysis was successful in disclosing the different patterns of brain activity associated with hypothesis triggering and handling (pattern P1); identification uncertainty and prevalence assessment (pattern P3), and hypothesis plausibility calculation (pattern P2); Logistic regression analysis was successful in disclosing the brain activity associated with clinical reasoning success, and together with regression analysis showed that clinical practice reorganizes the neural circuits supporting clinical reasoning.

Development of a new approach to aid in visual identification of murine iPS colonies using a fuzzy logic decision support system.

The a priori identification of induced pluripotent stem cells remains a challenge. Being able to quickly identify the most embryonic stem cell-similar induced pluripotent stem cells when validating results could help to reduce costs and save time. In this context, tools based on non-classic logic can be useful in creating aid-systems based on visual criteria. True colonies when viewed at 100x magnification have been found to have the following 3 characteristics: a high degree of border delineation, a more uniform texture, and the absence of a cracked texture. These visual criteria were used for fuzzy logic modeling. We investigated the possibility of predicting the presence of alkaline phosphatase activity, typical of true induced pluripotent stem cell colonies, after 25 individuals, with varying degrees of experience in working with murine iPS cells, categorized the images of 136 colonies based on visual criteria. Intriguingly, the performance evaluation by area under the ROC curve (16 individuals with satisfactory performance), Spearman correlation (all statistically significant), and Cohen's Kappa agreement analysis (all statistically significant) demonstrates that the discriminatory capacity of different evaluators are similar, even those who have never cultivated cells. Thus, we report on a new system to facilitate visual identification of murine- induced pluripotent stem cell colonies that can be useful for staff training and opens the possibility of exploring visual characteristics of induced pluripotent stem cell colonies with their functional peculiarities. The fuzzy model has been integrated as a web-based tool named "2see-iPS" which is freely accessed at http://genetica.incor.usp.br/2seeips/.

Application of a model based on fuzzy logic for evaluating nursing diagnostic accuracy of students.

PURPOSE: To describe a model for assessing nursing diagnostic accuracy and its application to undergraduate students, comparing students' performance according to the course year. METHODS: This model, based on the theory of fuzzy sets, guides a student through three steps: (a) the student must parameterize the model by establishing relationship values between defining characteristic/risk factors and nursing diagnoses; (b) presentation of a clinical case; (c) the student must define the presence of each defining characteristic/risk factors for the clinical case. Subsequently, the model computes the most plausible diagnoses by taking into account the values indicated by the student. This gives the student a performance score in comparison with parameters and diagnoses that were previously provided by nursing experts. These nursing experts collaborated with the construction of the model indicating the strength of the relationship between the concepts, meaning, they parameterized the model to compare the student's choice with the expert's choice (gold standard), thus generating performance scores for the student. The model was tested using three clinical cases presented to 38 students in their third and fourth years of the undergraduate nursing course. RESULTS: Third year students showed superior performance in identifying the presence of defining characteristic/risk factors, while fourth year students showed superior performance in the diagnoses by the model. CONCLUSIONS: The Model for Evaluation of Diagnostic Accuracy Based on Fuzzy Logic applied in this study is feasible and can be used to evaluate students' performance. In this regard, it will open a broad variety of applications for learning and nursing research. LIMITATIONS: Despite the ease in filling the printed questionnaires out, the number of steps and fields to fill in may explain the considerable number of questionnaires with incorrect or missing data. This was solved in the digital version of the questionnaire. In addition, in more complex cases, it is possible that an expert opinion can lead to a wrong decision due to the subjectivity of the diagnostic process.

Support system for decision making in the identification of risk for body dysmorphic disorder: a fuzzy model.

PURPOSE: To develop a fuzzy linguistic model to quantify the level of distress of patients seeking cosmetic surgery. Body dysmorphic disorder (BDD) is a mental condition related to body image relatively common among cosmetic surgery patients; it is difficult to diagnose and is a significant cause of morbidity and mortality. Fuzzy cognitive maps are an efficient tool based on human knowledge and experience that can handle uncertainty in identifying or grading BDD symptoms and the degree of body image dissatisfaction. Individuals who seek cosmetic procedures suffer from some degree of dissatisfaction with appearance. METHODS: A fuzzy model was developed to measure distress levels in cosmetic surgery patients based on the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), diagnostic criterion B for BDD. We studied 288 patients of both sexes seeking abdominoplasty, rhinoplasty, or rhytidoplasty in a university hospital. RESULTS: Patient distress ranged from "none" to "severe" (range=7.5-31.6; cutoff point=18; area under the ROC curve=0.923). There was a significant agreement between the fuzzy model and DSM-IV criterion B (kappa=0.805; p<0.001). CONCLUSION: The fuzzy model measured distress levels with good accuracy, indicating that it can be used as a screening tool in cosmetic surgery and psychiatric practice.

Fuzzy cognitive map in differential diagnosis of alterations in urinary elimination: a nursing approach.

PURPOSE: To develop a decision support system to discriminate the diagnoses of alterations in urinary elimination, according to the nursing terminology of NANDA International (NANDA-I). METHODS: A fuzzy cognitive map (FCM) was structured considering six possible diagnoses: stress urinary incontinence, reflex urinary incontinence, urge urinary incontinence, functional urinary incontinence, total urinary incontinence and urinary retention; and 39 signals associated with them. The model was implemented in Microsoft Visual C++(®) Edition 2005 and applied in 195 real cases. Its performance was evaluated through the agreement test, comparing its results with the diagnoses determined by three experts (nurses). The sensitivity and specificity of the model were calculated considering the expert's opinion as a gold standard. In order to compute the Kappa's values we considered two situations, since more than one diagnosis was possible: the overestimation of the accordance in which the case was considered as concordant when at least one diagnoses was equal; and the underestimation of the accordance, in which the case was considered as discordant when at least one diagnosis was different. RESULTS: The overestimation of the accordance showed an excellent agreement (kappa=0.92, p<0.0001); and the underestimation provided a moderate agreement (kappa=0.42, p<0.0001). In general the FCM model showed high sensitivity and specificity, of 0.95 and 0.92, respectively, but provided a low specificity value in determining the diagnosis of urge urinary incontinence (0.43) and a low sensitivity value to total urinary incontinence (0.42). CONCLUSIONS: The decision support system developed presented a good performance compared to other types of expert systems for differential diagnosis of alterations in urinary elimination. Since there are few similar studies in the literature, we are convinced of the importance of investing in this kind of modeling, both from the theoretical and from the health applied points of view. LIMITATIONS: In spite of the good results, the FCM should be improved to identify the diagnoses of urge urinary incontinence and total urinary incontinence.

Ecosystem approach and the Fuzzy logic: a dialectical proposal for information on Environmental Health / Abordagem ecossistêmica e lógica Fuzzy: uma proposta dialética para o uso da informação em Saúde Ambiental

The ever-growing production and the problematization of Environmental Health have shown the need to apprehend complex realities and deal with uncertainties from the most diversified instruments which may even incorporate local aspects and subjectivities by means of qualitative realities, while broadening the capacity of the information system. This paper presents a view on the reflection upon some challenges and possible convergences between the ecosystemic approach and the Fuzzy logic in the process of dealing with scientific information and decision-making in Environmental Health.

O avanço da produção intelectual sobre Saúde e Ambiente tem demonstrado a necessidade de apreender realidades que são complexas, além de lidar com suas incertezas. Nesse sentido, os instrumentos utilizados deveriam incorporar aspectos subjetivos e qualitativos, além dos elementos de cunho quantitativo, ao retratar uma condição local. Esse artigo apresenta uma reflexão a respeito dos desafios e dos possíveis pontos de convergência entre uma abordagem ecossistêmica e a lógica Fuzzy nesse processo de lidar com a informação para apoio a tomada de decisão envolvendo Saúde e Ambiente.

Software application that evaluates the diagnostic accuracy of nursing students.

PURPOSE: Apply the educational software Fuzzy Kitten with undergraduate Brazilian nursing students. METHODS: This software, based on fuzzy logic, generates performance scores that evaluate the ability to identify defining characteristics/risk factors present in clinical cases, relate them with nursing diagnoses, and determine the diagnoses freely or using a decision support model. FINDINGS: There were differences in student performance compared to the year of the course. The time to perform the activity did not present a significant relation to the performance. The students' scores in the diagnoses indicated by the model was superior (p= .01). CONCLUSIONS: The software was able to evaluate the diagnostic accuracy of students. IMPLICATIONS: The software enables an objective evaluation of diagnostic accuracy.

[The development and evaluation of software to verify diagnostic accuracy]. / Desenvolvimento e avaliação de um software que verifica a acurácia diagnóstica.

This article describes the development and evaluation of software that verifies the accuracy of diagnoses made by nursing students. The software was based on a model that uses fuzzy logic concepts, including PERL, the MySQL database for Internet accessibility, and the NANDA-I 2007-2008 classification system. The software was evaluated in terms of its technical quality and usability through specific instruments. The activity proposed in the software involves four stages in which students establish the relationship values between nursing diagnoses, defining characteristics/risk factors and clinical cases. The relationship values determined by students are compared to those of specialists, generating performance scores for the students. In the evaluation, the software demonstrated satisfactory outcomes regarding the technical quality and, according to the students, helped in their learning and may become an educational tool to teach the process of nursing diagnosis.

Desenvolvimento e avaliação de um software que verifica a acurácia diagnóstica / The development and evaluation of software to verify diagnostic accuracy / Desarrollo y evaluación de un software que verifica la exactitud diagnóstica

Este artigo descreve o desenvolvimento e avaliação de um software que verifica a acurácia diagnóstica de alunos de enfermagem. O software foi baseado num modelo que utiliza conceitos da lógica fuzzy, em PERL, banco de dados MySQL para acesso pela internet e a classificação NANDA-I 2007-2008. Avaliou-se a qualidade técnica e a usabilidade do software utilizando instrumentos específicos. A atividade proposta no software possui quatro etapas nas quais o aluno estabelece valores de relação entre diagnósticos de enfermagem, características definidoras/fatores de risco e casos clínicos. Os valores de relação determinados pelo aluno são comparados aos de especialistas, gerando escores de desempenho para o aluno. Na avaliação, o software atendeu satisfatoriamente as necessidades de qualidade técnica e, segundo os alunos, trouxe benefícios ao aprendizado, podendo transformar-se em uma ferramenta educacional no ensino do diagnóstico de enfermagem.

This article describes the development and evaluation of software that verifies the accuracy of diagnoses made by nursing students. The software was based on a model that uses fuzzy logic concepts, including PERL, the MySQL database for Internet accessibility, and the NANDA-I 2007-2008 classification system. The software was evaluated in terms of its technical quality and usability through specific instruments. The activity proposed in the software involves four stages in which students establish the relationship values between nursing diagnoses, defining characteristics/risk factors and clinical cases. The relationship values determined by students are compared to those of specialists, generating performance scores for the students. In the evaluation, the software demonstrated satisfactory outcomes regarding the technical quality and, according to the students, helped in their learning and may become an educational tool to teach the process of nursing diagnosis.

Este artículo describe el desarrollo y evaluación de un software que verifica la exactitud diagnóstica de alumnos de enfermería. El software se basó en un modelo que utiliza conceptos de lógica fuzzy, en PERL, banco de datos MySQL para acceso por Internet y la clasificación NANDA-I 2007-2008. Se evaluó calidad técnica y usabilidad del software utilizando instrumentos específicos. La actividad propuesta en el software consiste en cuatro etapas, en las que el alumno establece valores de relación entre diagnósticos de enfermería, características de definición/factores de riesgo y casos clínicos. Los valores de relación determinados por el alumno son comparados con los de especialistas, generando puntajes de desempeño del alumno. En la evaluación, el software atendió satisfactoriamente las necesidades de calidad técnica y mostró que, en la percepción de los alumnos, trajo beneficios de aprendizaje, pudiendo transformarse en una herramienta educativa en la enseñanza del diagnóstico de enfermería.

The use of expert systems on the differential diagnosis of urinary incontinence.

The differential diagnosis of urinary incontinence classes is sometimes difficult to establish. As a rule, only the results of urodynamic testing allow an accurate diagnosis. However, this exam is not always feasible, because it requires special equipment, and also trained personnel to lead and interpret the exam. Some expert systems have been developed to assist health professionals in this field. Therefore, the aims of this paper are to present the definition of Artificial Intelligence; to explain what expert system and system for decision support are and its application in the field of health and to discuss some expert systems for differential diagnosis of urinary incontinence. It is concluded that expert systems may be useful not only for teaching purposes, but also as decision support in daily clinical practice. Despite this, for several reasons, health professionals usually hesitate to use the computer expert system to support their decision making process.

The use of expert systems on the differential diagnosis of urinary incontinence / Uso de sistemas especialistas para o diagnóstico diferencial de incontinência urinária / Uso de los sistemas especialistas en el diagnóstico diferencial de la incontinencia urinaria

The differential diagnosis of urinary incontinence classes is sometimes difficult to establish. As a rule, only the results of urodynamic testing allow an accurate diagnosis. However, this exam is not always feasible, because it requires special equipment, and also trained personnel to lead and interpret the exam. Some expert systems have been developed to assist health professionals in this field. Therefore, the aims of this paper are to present the definition of Artificial Intelligence; to explain what Expert System and System for Decision Support are and its application in the field of health and to discuss some expert systems for differential diagnosis of urinary incontinence. It is concluded that expert systems may be useful not only for teaching purposes, but also as decision support in daily clinical practice. Despite this, for several reasons, health professionals usually hesitate to use the computer expert system to support their decision making process.

O diagnóstico diferencial dos tipos de incontinência urinária é algumas vezes difícil de estabelecer. Via de regra, somente os resultados de exames urodinâmicos permitem um diagnóstico acurado. Entretanto, esse exame nem sempre é factível, porque requer equipamento especial e também pessoal treinado para realizar e interpretar o exame. Alguns sistemas especialistas têm sido desenvolvidos para assistir profissionais que atuam nessa área. Propõe-se aqui apresentar a definição de inteligência artificial; explicar o que são sistemas especialistas, sistemas de apoio à decisão e sua aplicação na área da saúde e, discutir alguns sistemas especialistas desenvolvidos para o diagnóstico diferencial da incontinência urinária. Conclui-se que esses sistemas podem ser úteis não somente para o ensino, mas também como apoio à decisão na prática clínica diária. A despeito disso, por várias razões, os profissionais de saúde usualmente hesitam em usar o sistema especialista computacional para dar suporte ao processo de decisão.

El diagnóstico diferencial de los tipos de incontinencia urinaria es algunas veces difícil. En general, solamente los resultados de exámenes urodinâmicos permiten uno diagnóstico preciso. Entretanto, no es siempre posible hacer ése examen porque requiere equipo especial y personal entrenado hacia realizar y interpretar lo examen. Sistemas especialistas tienen sido hechos hacia asistir los profesionales de salud en ese campo. Propone-se presentar aquí lo que es inteligencia artificial; explicar lo que son sistemas especialistas, sistemas hacia apoyo a la decisión y suya aplicación en el área de la salud y discutir sistemas especialistas hacia el diagnóstico diferencial de la incontinencia. Concluye-se que los sistemas especialistas puedan ser usados no solamente hacia la enseñanza, mas también como apoyo a la decisión en la práctica clínica. A pesar de eso, por varias razones, profesionales de salud usualmente resisten en emplear el sistema especialista computacional hacia dar soporte al proceso de decisión.

Fuzzy modeling of electrical impedance tomography images of the lungs.

OBJECTIVES: Aiming to improve the anatomical resolution of electrical impedance tomography images, we developed a fuzzy model based on electrical impedance tomography's high temporal resolution and on the functional pulmonary signals of perfusion and ventilation. INTRODUCTION: Electrical impedance tomography images carry information about both ventilation and perfusion. However, these images are difficult to interpret because of insufficient anatomical resolution, such that it becomes almost impossible to distinguish the heart from the lungs. METHODS: Electrical impedance tomography data from an experimental animal model were collected during normal ventilation and apnea while an injection of hypertonic saline was administered. The fuzzy model was elaborated in three parts: a modeling of the heart, the pulmonary ventilation map and the pulmonary perfusion map. Image segmentation was performed using a threshold method, and a ventilation/perfusion map was generated. RESULTS: Electrical impedance tomography images treated by the fuzzy model were compared with the hypertonic saline injection method and computed tomography scan images, presenting good results. The average accuracy index was 0.80 when comparing the fuzzy modeled lung maps and the computed tomography scan lung mask. The average ROC curve area comparing a saline injection image and a fuzzy modeled pulmonary perfusion image was 0.77. DISCUSSION: The innovative aspects of our work are the use of temporal information for the delineation of the heart structure and the use of two pulmonary functions for lung structure delineation. However, robustness of the method should be tested for the imaging of abnormal lung conditions. CONCLUSIONS: These results showed the adequacy of the fuzzy approach in treating the anatomical resolution uncertainties in electrical impedance tomography images.

Fuzzy modeling of electrical impedance tomography images of the lungs

OBJECTIVES: Aiming to improve the anatomical resolution of electrical impedance tomography images, we developed a fuzzy model based on electrical impedance tomography's high temporal resolution and on the functional pulmonary signals of perfusion and ventilation. INTRODUCTION: Electrical impedance tomography images carry information about both ventilation and perfusion. However, these images are difficult to interpret because of insufficient anatomical resolution, such that it becomes almost impossible to distinguish the heart from the lungs. METHODS: Electrical impedance tomography data from an experimental animal model were collected during normal ventilation and apnea while an injection of hypertonic saline was administered. The fuzzy model was elaborated in three parts: a modeling of the heart, the pulmonary ventilation map and the pulmonary perfusion map. Image segmentation was performed using a threshold method, and a ventilation/perfusion map was generated. RESULTS: Electrical impedance tomography images treated by the fuzzy model were compared with the hypertonic saline injection method and computed tomography scan images, presenting good results. The average accuracy index was 0.80 when comparing the fuzzy modeled lung maps and the computed tomography scan lung mask. The average ROC curve area comparing a saline injection image and a fuzzy modeled pulmonary perfusion image was 0.77. DISCUSSION: The innovative aspects of our work are the use of temporal information for the delineation of the heart structure and the use of two pulmonary functions for lung structure delineation. However, robustness of the method should be tested for the imaging of abnormal lung conditions. CONCLUSIONS: These results showed the adequacy of the fuzzy approach in treating the anatomical resolution uncertainties in electrical impedance tomography images.

Fuzzy logic model based on the differential nursing diagnosis of alterations in urinary elimination.

The nursing diagnoses associated with alterations in urinary elimination require different interventions, and nurses who are not specialists need support to diagnose and to manage patients with disturbances of urine elimination. The aim of this study was to present a model based on fuzzy logic for making differential diagnosis of alterations in urinary elimination, considering the nursing diagnosis approved by the North American Nursing Diagnosis Association (NANDA), 2001-2002. The fuzzy maximum-minimum composition was used to develop this model. It was tested with 195 cases from a database of a previous study. The model was able to determine the diagnosis in total accordance with a panel of three experts for 79.5% of the cases. The model diagnosed 19% of the cases with partial concordance with the panel of experts. Only for 3 cases (1.5%) the model showed a different diagnosis. It is concluded that the model proposed here, despite of its simplicity, presents good performance. However, it is recommended more tests before widely used as support for clinical decision.

Fuzzy epidemics.

The purpose of this paper is to provide a review of the current state of fuzzy logic theory in epidemiology, which is a recent area of research. We present four applications of fuzzy logic theory in epidemic problems, using linguistic fuzzy models, possibility measure, probability of fuzzy events and fuzzy decision making techniques. The results demonstrate that the applications of fuzzy sets in epidemiology is a very promising area of research. The final discussion sets the future stage of fuzzy sets application in epidemiology.