Sistemas de expertos desarrollados en el mundo para la detección, el diagnóstico y el tratamiento del cáncer / Expert systems developed worldwide to detect, diagnose and treat cancer

Dentro de las ramas de la Inteligencia Artificial se encuentran los sistemas de expertos, definidos como sistemas informáticos que simulan el proceso de aprendizaje, de memorización, de razonamiento, de comunicación y de acción en consecuencia de un experto humano en cualquier rama de la ciencia para resolver problemas. El presente trabajo tuvo como objetivo caracterizar algunos sistemas de expertos desarrollados internacionalmente para la detección, el diagnóstico y el tratamiento del cáncer. Para lograrlo se realizó una exhaustiva revisión bibliográfica en Internet a través de las bases de datos EBSCO, PubMed y SciELO, priorizando los artículos originales y las revisiones bibliográficas. Los 12 artículos seleccionados corresponden en su mayoría a tesis de Terminación de Grado y a artículos publicados en la Base de Datos SciELO. Los sistemas expuestos en nuestra investigación fueron concebidos a partir de la simulación de casos prácticos, de los análisis de documentos y de la información obtenida en varias entrevistas presenciales, diseñados en un entorno web para garantizar el acceso en línea de especialistas, estudiantes y de los propios pacientes, en algunos casos con un nivel de acierto que osciló entre el 87 y el 100 por ciento. Además, tienen en común la funcionalidad de establecer la probabilidad de que un paciente padezca o no de cáncer, independientemente de su localización, teniendo en cuenta la presencia de signos o síntomas asociados a la enfermedad, así como la de favorecer la detección de un diagnóstico temprano para la determinación de un tratamiento eficaz(AU)

Expert systems belong in the field of artificial intelligence. They are defined as information systems that simulate the process of learning, memorizing, reasoning, communicating and consequent acting of a human expert in any field of science with the aim of solving problems. The purpose of the study was to characterize the expert systems developed worldwide to detect, diagnose and treat cancer. To achieve such an end, an exhaustive bibliographic review was conducted in the Internet databases EBSCO, PubMed and SciELO, prioritizing original papers and bibliographic reviews. Most of the 12 papers selected are diploma theses and publications from the database SciELO. The systems included in our research were conceived of based on simulation of practical cases, document analysis and information obtained from a number of live interviews designed in an Internet environment to ensure online access by specialists, students and the patients themselves, in some cases with an accuracy level ranging from 87 percent to 100 percent. They also exhibit the common functionality of establishing the probability that a patient may or may not suffer from cancer, regardless of their location, bearing in mind the presence of signs or symptoms associated to the disease and fostering detection of an early diagnosis to determine an efficient treatment(AU)

Research progress and prospect of expert system for vertigo disease / 第二军医大学学报

In recent years, artificial intelligence technology in medical field has become a research focus of modern science and technology. The application of artificial intelligence technology in the diagnosis of dizziness can not only save medical resources, but also treat dizziness in time. In this paper, we analyzed the application of artificial intelligence technology in the field of vertigo diagnosis by illuminating the expert systems for vertigo disease such as “Vertigo” and “ONE”, and other methods, summarized the advantages and disadvantages of various artificial intelligence methods applied in vertigo disease, and prospected the development prospect of artificial intelligence technology in vertigo diagnosis system.

ILITIA: telehealth architecture for high-risk gestation classification

Abstract Introduction According to the World Health Organization, about 9.2% of the 28 million newborns worldwide are stillborn. Besides, about 358,000 women died due to complications related to pregnancy in 2015. Part of these deaths could have been avoided with improving prenatal care agility to recognize problems during pregnancy. Based on that, many efforts have been made to provide technologies that can contribute to offer better access to information and assist in decision-making. In this context, this work presents an architecture to automate the classification and referral process of pregnant women between the basic health units and the referral hospital through a Telehealth platform. Methods The Telehealth architecture was developed in three components: The data acquisition component, responsible for collecting and inserting data; the data processing component, which is the core of the architecture implemented using expert systems to classify gestational risk; and the post-processing component, in charge of the delivery and analysis of cases. Results Acceptance test, system accuracy test based on rules and performance test were realized. For the tests, 1,380 referral forms of real situations were used. Conclusion On the results obtained with the analysis of real data, ILITIA, the developed architecture has met the requirements to assist medical specialists on gestational risk classification, which decreases the inconvenience of pregnant women displacement and the resulting costs.

A computer-aided diagnostic system for kidney disease

BACKGROUND: Disease diagnosis is complicated since patients may demonstrate similar symptoms but physician may diagnose different diseases. There are a few number of investigations aimed to create a fuzzy expert system, as a computer aided system for disease diagnosis. METHODS: In this research, a cross-sectional descriptive study conducted in a kidney clinic in Tehran, Iran in 2012. Medical diagnosis fuzzy rules applied, and a set of symptoms related to the set of considered diseases defined. The input case to be diagnosed defined by assigning a fuzzy value to each symptom and then three physicians asked about each suspected diseases. Then comments of those three physicians summarized for each disease. The fuzzy inference applied to obtain a decision fuzzy set for each disease, and crisp decision values attained to determine the certainty of existence for each disease. RESULTS: Results indicated that, in the diagnosis of seven cases of kidney disease by examining 21 indicators using fuzzy expert system, kidney stone disease with 63% certainty was the most probable, renal tubular was at the lowest level with 15%, and other kidney diseases were at the other levels. The most remarkable finding of this study was that results of kidney disease diagnosis (e.g., kidney stone) via fuzzy expert system were fully compatible with those of kidney physicians. CONCLUSION: The proposed fuzzy expert system is a valid, reliable, and flexible instrument to diagnose several typical input cases. The developed system decreases the effort of initial physical checking and manual feeding of input symptoms.

Healthcare Decision Support System for Administration of Chronic Diseases / 대한의료정보학회지

OBJECTIVES: A healthcare decision-making support model and rule management system is proposed based on a personalized rule-based intelligent concept, to effectively manage chronic diseases. METHODS: A Web service was built using a standard message transfer protocol for interoperability of personal health records among healthcare institutions. An intelligent decision service is provided that analyzes data using a service-oriented healthcare rule inference function and machine-learning platform; the rules are extensively compiled by physicians through a developmental user interface that enables knowledge base construction, modification, and integration. Further, screening results are visualized for the self-intuitive understanding of personal health status by patients. RESULTS: A recommendation message is output through the Web service by receiving patient information from the hospital information recording system and object attribute values as input factors. The proposed system can verify patient behavior by acting as an intellectualized backbone of chronic diseases management; further, it supports self-management and scheduling of screening. CONCLUSIONS: Chronic patients can continuously receive active recommendations related to their healthcare through the rule management system, and they can model the system by acting as decision makers in diseases management; secondary diseases can be prevented and health management can be performed by reference to patient-specific lifestyle guidelines.

Sistema especialista para apoiar a decisão na terapia tópica de úlceras venosas / Expert system to support the decision in topical therapy for venous ulcers / Sistema especialita para apoyar la decisión en la terapia tópica de úlceras venosas

Apesar de o tratamento das úlceras venosas exigir um conjunto de conhecimentos específicos, os enfermeiros não especialistas desconhecem as terapias adequadas, o que constitui uma dificuldade na terapia tópica dessas lesões de pele. Este artigo tem como objetivo apresentar um sistema especialista para apoiar o processo de decisão dos enfermeiros na terapia tópica das úlceras venosas. Trata-se de uma pesquisa de desenvolvimento, operacionalizada em cinco etapas: modelagem do sistema, aquisição do conhecimento, representação do conhecimento a partir de regras de produção, implementação e avaliação do sistema. O conjunto das regras é apresentado, assim como casos que simulam o comportamento do sistema especialista, mostrando a viabilidade da sua utilização na prática do enfermeiro. O sistema poderá auxiliar na tomada de decisão sobre as condutas tópicas em úlceras venosas, porém, a avaliação da úlcera deve ser realizada de forma correta, a fim de que o sistema forneça sugestões adequadas, permitindo melhor organização e planejamento da assistência.

Although the treatment of venous ulcers requires a set of specific knowledge, non-specialist nurses are unaware of the appropriate therapy, which is a concern in the topical therapy for these skin lesions. This paper aims to present an expert system to support the nursing decision making process in the topical therapy of venous ulcers. It is a development research implemented in five stages: system modeling, knowledge acquisition, knowledge representation from production rules, and system implementation and evaluation. The production rules are presented, as well as some cases to simulate the expert system behavior, demonstrating the viability of its usage in nurse's practice. The system may support the decision making about the topical therapy of venous ulcers. However, ulcer evaluation should be correctly made, so that the system provides appropriate suggestions, allowing better organization and planning assistance.

Aunque el tratamiento de las úlceras venosas exige un conjunto de conocimientos específicos, los enfermeros no especializados desconocen la terapia adecuada, lo que constituye una dificultad en la terapia tópica de esas lesiones de piel. Este artículo tiene como objetivo presentar un sistema especializado para apoyar el proceso de decisión de los enfermeros en la terapia tópica de las úlceras venosas. Se trata de una investigación del desarrollo, operado en cinco etapas: modelaje del sistema, adquisición de conocimientos, representación del conocimiento a partir de reglas de producción, de implementación y evaluación del sistema. El conjunto de reglas es presentado, así como algunos casos que simulan el comportamiento del sistema especializado. El sistema puede ayudar a tomar decisiones sobre la terapia tópica, pero, la evaluación de la úlcera se debe realizar correctamente para que el sistema proporcione sugerencias adecuadas, lo que permite una mejor organización y planificación de la asistencia.

Development and Application of a Web-based Expert System using Artificial Intelligence for Management of Mental Health by Korean Emigrants

PURPOSE: The purpose of this project was to develop an international web-based expert system using principals of artificial intelligence and user-centered design for management of mental health by Korean emigrants. Using this system, anyone can access the system via computer access to the web. METHODS: Our design process utilized principles of user-centered design with 4 phases: needs assessment, analysis, design/development/testing, and application release. A survey was done with 3,235 Korean emigrants. Focus group interviews were also conducted. Survey and analysis results guided the design of the web-based expert system. RESULTS: With this system, anyone can check their mental health status by themselves using a personal computer. The system analyzes facts based on answers to automated questions, and suggests solutions accordingly. A history tracking mechanism enables monitoring and future analysis. In addition, this system will include intervention programs to promote mental health status. CONCLUSION: This system is interactive and accessible to anyone in the world. It is expected that this management system will contribute to Korean emigrants' mental health promotion and allow researchers and professionals to share information on mental health.

Developing a Biomedical Expert Finding System Using Medical Subject Headings / 대한의료정보학회지

OBJECTIVES: Efficient identification of subject experts or expert communities is vital for the growth of any organization. Most of the available expert finding systems are based on self-nomination, which can be biased, and are unable to rank experts. Thus, the objective of this work was to develop a robust and unbiased expert finding system which can quantitatively measure expertise. METHODS: Medical Subject Headings (MeSH) is a controlled vocabulary developed by the National Library of Medicine (NLM) for indexing research publications, articles and books. Using the MeSH terms associated with peer-reviewed articles published from India and indexed in PubMed, we developed a Web-based program which can be used to identify subject experts and subjects associated with an expert. RESULTS: We have extensively tested our system to identify experts from India in various subjects. The system provides a ranked list of experts where known experts rank at the top of the list. The system is general; since it uses information available with the PubMed, it can be implemented for any country. CONCLUSIONS: The expert finding system is able to successfully identify subject experts in India. Our system is unique because it allows the quantification of subject expertise, thus enabling the ranking of experts. Our system is based on peer-reviewed information. Use of MeSH terms as subjects has standardized the subject terminology. The system matches requirements of an ideal expert finding system.

Aplicaciones médicas como ayuda al diagnóstico en la medicina. Experiencia SOFTEL-MINSAP / Medical application for support of diagnosis in medicine. SOFTEL-MINSAP experience

La Inteligencia Artificial (IA) en una primera aproximación, se puede definir como la rama de la computación que estudia la automatización del comportamiento inteligente. La investigación en este campo ha llevado al desarrollo de herramientas computacionales específicas, entre las cuales se cuentan una gran diversidad de formalismos de representación de conocimientos y de algoritmos que los aplican, además de los lenguajes, estructuras de datos y técnicas de programación utilizados para su implementación. Este mecanismo es el que intentan imitar los programas de inteligencia artificial llamados sistemas expertos o sistemas basados en el conocimiento. La Empresa SOFTEL, perteneciente al Ministerio de la Informática y las Comunicaciones (MIC), desde sus inicios desarrolló la informática médica, y dentro de ésta la rama de Inteligencia Artificial en aplicaciones como INFOTOXI, encargado de controlar y diagnosticar intoxicación por productos tóxicos en centros dedicados a este tema; GERISOFT, para la Atención Primaria de Salud del adulto mayor y el SEAA, Sistema de Ayuda Diagnóstica en la Asistencia Primaria. Para desarrollar estos sistemas se apoyaron en el conocimiento de médicos especialistas del Ministerio de Salud Pública (MINSAP) en calidad de expertos. Dichos sistemas fueron instalados en diferentes unidades del sistema de salud(AU)

Artificial Intelligence (AI) in a first approximation can be defined as the branch of computer science that studies the automation of intelligent behavior. This research has led to the development of specific computational tools, which include a wide range of knowledge representation formalisms and related algorithms, in addition to the language of data structures and programming techniques used for its implementation. This mechanism is attempting to imitate the programs of artificial intelligence known as expert systems or knowledge-based systems. Softel Company, owned by the Ministry of Informatics and Communications (MIC), from its inception has developed medical informatics within this branch of artificial intelligence in applications such as INFOTOXI, in charge of monitoring and diagnosing poisoning by toxic products in centers devoted to this theme; GER-ISOFT, for Primary Health Care for the elderly and SAAS System Diagnostic Support in Primary Care. The development of these systems was supported in the knowledge of specialist doctors from the Ministry of Public Health of Cuba (MINSAP), in quality of experts in their respective subjects. These systems are deployed in different units of the health system(AU)

Classification of the severity of diabetic neuropathy: a new approach taking uncertainties into account using fuzzy logic

OBJECTIVE: This study proposes a new approach that considers uncertainty in predicting and quantifying the presence and severity of diabetic peripheral neuropathy. METHODS: A rule-based fuzzy expert system was designed by four experts in diabetic neuropathy. The model variables were used to classify neuropathy in diabetic patients, defining it as mild, moderate, or severe. System performance was evaluated by means of the Kappa agreement measure, comparing the results of the model with those generated by the experts in an assessment of 50 patients. Accuracy was evaluated by an ROC curve analysis obtained based on 50 other cases; the results of those clinical assessments were considered to be the gold standard. RESULTS: According to the Kappa analysis, the model was in moderate agreement with expert opinions. The ROC analysis (evaluation of accuracy) determined an area under the curve equal to 0.91, demonstrating very good consistency in classifying patients with diabetic neuropathy. CONCLUSION: The model efficiently classified diabetic patients with different degrees of neuropathy severity. In addition, the model provides a way to quantify diabetic neuropathy severity and allows a more accurate patient condition assessment.

Expert System Shells for Rapid Clinical Decision Support Module Development: An ESTA Demonstration of a Simple Rule-Based System for the Diagnosis of Vaginal Discharge / 대한의료정보학회지

OBJECTIVES: This study demonstrates the feasibility of using expert system shells for rapid clinical decision support module development. METHODS: A readily available expert system shell was used to build a simple rule-based system for the crude diagnosis of vaginal discharge. Pictures and 'canned text explanations' are extensively used throughout the program to enhance its intuitiveness and educational dimension. All the steps involved in developing the system are documented. RESULTS: The system runs under Microsoft Windows and is available as a free download at http://healthcybermap.org/vagdisch.zip (the distribution archive includes both the program's executable and the commented knowledge base source as a text document). The limitations of the demonstration system, such as the lack of provisions for assessing uncertainty or various degrees of severity of a sign or symptom, are discussed in detail. Ways of improving the system, such as porting it to the Web and packaging it as an app for smartphones and tablets, are also presented. CONCLUSIONS: An easy-to-use expert system shell enables clinicians to rapidly become their own 'knowledge engineers' and develop concise evidence-based decision support modules of simple to moderate complexity, targeting clinical practitioners, medical and nursing students, as well as patients, their lay carers and the general public (where appropriate). In the spirit of the social Web, it is hoped that an online repository can be created to peer review, share and re-use knowledge base modules covering various clinical problems and algorithms, as a service to the clinical community.

Sistema de auxílio aos diagnósticos de enfermagem para vítimas detrauma no atendimento avançado pré-hospitalar móvel utilizando asTaxonomias NANDA e NIC / Computer-aided diagnosis system to the nursing diagnosis of trauma victims in mobile pre-hospital careusing the NANDA and NIC Taxonomies

Uma das metodologias habituais para elaboração do Diagnóstico de Enfermagem é a utilização de consulta manual à taxonomia NANDA (North American Nursing Diagnosis Association), quase sempre argumentada como morosa e de difícil aplicabilidade prática. Contudo, para auxiliar no processo de diagnóstico em enfermagem, principalmente em situações de emergência é viável a utilização de uma ferramenta computacional, que pode reduzir o período para sua efetivação, permitindo ao enfermeiro disponibilizar mais tempo para o cuidado humanizado ao paciente vítima de trauma. O objetivo desse trabalho é desenvolver um sistema de auxílio à tomada de decisão sobre os diagnósticos de enfermagem em vítimas de trauma no atendimento avançado pré-hospitalar móvel considerando a Taxonomia NANDA (North American Nursing Diagnoses Association), bem como propor a intervenção a ser realizada baseando-se na NIC (Nursing Interventions Classification). Para o desenvolvimento da aplicação utilizou-se o sistema operacional Windows XP Professional, a linguagem de programação PHP (Hypertext Preprocessor) e o servidor Web Apache HTTP Server. Todavia, os dados foram gerenciados pelo Sistema Gerenciador de Banco de Dados Oracle Enterprise Edition release 8.1.7. Para validar o sistema realizou-se uma avaliação qualitativa com usuários. Os resultados apresentados indicam que as informações são gerenciadas e armazenadas corretamente, bem como o tempo de retorno das informações é ideal, tanto para a consulta do diagnóstico como para a consulta das intervenções. Assim, é possível concluir que o sistema implementado é viável aos profissionais de enfermagem, contribuindo na otimização do tempo despendido para a elaboração do diagnóstico de enfermagem de clientes vítimas de trauma.

One of the methodologies in Nursing Diagnosis makes use of manual search through the NANDA taxonomy (North American Nursing Diagnoses Association), which is regarded as time-consuming and difficult to use in practice. However, in order to help conduct nursing diagnosis, particularly in the case of emergencies, the use of computers to assist the process is viable, which may limit manual search and allow the nurse to dedicate extra time to more humanized care to trauma victims. This study aims to develop an auxiliary system to decision-making in the nursing diagnosis of trauma victims in mobile pre-hospital care using the NANDA taxonomy as well as to recommend the applicable intervention according to the NIC (Nursing Interventions Classification). The Windows XP Professional operating system was used in the development of the software written in PHP (Hypertext Preprocessor). In addition, the Apache HTTP web server and the Oracle Enterprise Edition release 8.1.7 database manager have been used. In order to validate the system, users completed a qualitative assessment of the application. The findings show that information is stored and handled correctly, and that the time used to retrieve information is short in searches for both diagnoses and interventions. Thus, it is possible to conclude that the implemented system is beneficial to nursing professionals, contributing to the optimization of the time required to complete diagnosis and to plan nursing interventions concerning trauma patients.

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.

Avaliação de um sistema especialista em diagnóstico de enfermagem relacionados à eliminação urinária / Evaluación de un sistema especialista en diagnósticos de enfermeria relacionados a la eliminiación urinária / Evaluation of an expert system on nursing diagnoses related to urinary elimination

Foi desenvolvido e avaliado um sistema especialista em diagnósticos de enfermagem relacionados à eliminação urinária, segundo a taxionomia da NANDA. Para coleta de dados utilizou-se um roteiro e um checklist com as características definidoras. Os diagnósticos obtidos por consenso entre três especialistas foram considerados padrão-ouro. Foram testados 197 casos. O Sistema mostrou ser adequado para a determinação dos diagnósticos 'incontinência urinária (IU) por pressão', 'IU por impulso', 'retenção urinária ' e 'IU total', com sensibilidade e especificidade superiores a 98 por cento. A pequena casuística não possibilitou avaliar a acurácia em relação à 'eliminação urinária prejudicada', 'IU reflexa' e 'IU funcional'. Esta experiência de desenvolvimento e avaliação poderá ser aplicada na criação de outros sistemas especialistas.

An expert system on nursing diagnoses related to urinary elimination, according NANDA's taxonomy, was developed and evaluated. Data were collected using a form and a checklist of defining characteristics. The obtained consensus diagnoses by three specialists were considered gold standard. 197 cases were tested. The system proved to be adequate for determining diagnoses such as 'stress urinary incontinence', 'urge urinary incontinence', 'urinary retention' and 'total urinary incontinence' with sensitivity and specificity above 98 percent. The accuracy evaluation in relation to 'impaired urinary elimination', 'reflex urinary incontinence' and 'functional urinary incontinence' was not possible to be established due to the small size of the sample. The experience in developing and evaluating this program can be applied in creating other expert systems.

Fue desarrollado y avaluado un sistema especialista en diagnósticos relacionados a la eliminación urinaria, usando la taxonomia de NANDA. Para colectar los datos fue utilizado un programa de entrevista y un checklist conteniendo las características definidoras. Los diagnósticos obtenidos por concordancia de tres especialistas fueron considerados como prototipo-oro. Fueran testados 197 casos. El sistema desarrollado, mostró ser adecuado en la determinación de los diagnósticos 'incontinencia urinaria por presión', 'incontinencia urinaria por impulso', 'retención urinaria' e 'incontinencia urinaria total' con sensibilidad y especificidad superior a 98 por ciento. Debido a pequeña casuística, no fue posible avaluar los diagnósticos 'eliminación urinaria perjudicada', 'incontinencia urinaria refleja' e 'incontinencia urinaria funcional'. Esta experiencia de desenvolvimiento e avaluación podrá ser aplicada en la creación de otros sistemas.

Protótipo de um sistema especialista para a classificação da complexidade assistencial em enfermagem / An expert system prototype for the classification of the complexity of the assistance in nursing

This article is a study of the development of a System Specialist in Nursing, using Expert software SINTA (Applied Intelligent Systems), for the automatic classification of patients, in accordance with the degree of dependence of the team of nursing, based on Fugulin et al.

Este artigo é um estudo do desenvolvimento de um Sistema Especialista em Enfermagem, utilizando o software Expert SINTA (Sistemas Inteligentes Aplicados), para a classificação automática de pacientes, de acordo com o grau de dependência da equipe de enfermagem, baseado em Fugulin et al.

A Development of the Diagnosis Expert Systems for the Stroke Estimation / 대한의료정보학회지

In this study, we designed the expert system for the diagnosis of stroke. The causes of stroke in central nervous systems are very diverse, so a doctor who treats the patients with stroke must have the expert knowledge for the quick and correct diagnosis and for the adequate medical management. But the primary physician who engaged in the primary care of the patient with stroke does not have the expert knowledge for the stroke. So, we need to develop the expert system for assisting the diagnosis of stroke. Also the diagnosis system can be used as simulator for the medical students who study the neurology. In this study, we developed the diagnosis expert system that offer a pathological name provided by artificial neural networks. And we designed the inference engine and GUIs(graphical user interfaces). The artificial neural network is a system that provide a possible diagnosis of stroke. We implemented the system using Visual Basic 6.0 of Microsoft Co.