Diseño de sistema basado en reglas para apoyar la toma de decisiones de la población en la obtención de los medicamentos

En Cuba, el acceso a los servicios farmacéuticos por parte de la población se ve afectado por la no disponibilidad de medicamentos y la lejanía de las farmacias. La falta de información acerca de la existencia de los medicamentos y la cantidad de estos en la red de farmacias cercanas a una ubicación geográfica, aparejados al poco suministro de medicamentos y la calidad de la prestación del servicio, genera descontento e inconformidad en la población. En la presente investigación se realiza un diseño para mejorar la problemática planteada a partir de un sistema basado en reglas como ayuda a la toma de decisiones para la obtención de los medicamentos por parte de la población. Se aplica un estudio de caso mediante el cual es posible sugerir al usuario las 5 farmacias más cercanas donde el paciente puede adquirir los medicamentos sobre las decisiones asumidas.

In Cuba, access to pharmaceutical services by the population is affected by the non-availability of medicines and the remoteness of pharmacies. The lack of information about the existence of medicines and the quantity of these in the network of pharmacies close to a geographical location, coupled with the low supply of medicines and the quality of service provision, generates discontent and nonconformity in the population. In the present investigation, a design is carried out to improve the problem raised from a system based on rules as an aid to decision-making to obtain medicines by the population. A case study is applied through which it is possible to suggest to the user the 5 closest pharmacies where the patient can acquire the medicines on the decisions made.

Artificial intelligence-based drug development: current progress and future challenges / 中国药科大学学报

@#In recent years, artificial intelligence (AI) has been widely applied in the field of drug discovery and development.In particular, natural language processing technology has been significantly improved after the emergence of the pre-training model.On this basis, the introduction of graph neural network has also made drug development more accurate and efficient.In order to help drug developers more systematically and comprehensively understand the application of artificial intelligence in drug discovery, this article introduces cutting-edge algorithms in AI, and elaborates on the various applications of AI in drug development, including drug small molecule design, virtual screening, drug repurposing, and drug property prediction, finally discusses the opportunities and challenges of AI in future drug development.

Intelligent fault diagnosis expert system for multi-parameter monitor based on fault tree / 生物医学工程学杂志

Aiming at the dilemma of expensive and difficult maintenance, lack of technical data and insufficient maintenance force for modern medical equipment, an intelligent fault diagnosis expert system of multi-parameter monitor based on fault tree was proposed in this study. Firstly, the fault tree of multi-parameter monitor was established and analyzed qualitatively and quantitatively, then based on the analysis results of fault tree, the expert system knowledge base and inference engine were constructed and the overall framework of the system was determined, finally the intelligent fault diagnosis expert system for multi-parameter monitor was developed by using the page hypertext preprocessor (PHP) language, with an accuracy rate of 80% in fault diagnosis. The results showed that technology fusion on the basis of fault tree and expert system can effectively realize intelligent fault diagnosis of multi-parameter monitors and provide troubleshooting suggestions, which can not only provide experience accumulation for fault diagnosis of multi-parameter monitors, but also provide a new idea and technical support for fault diagnosis of medical equipment.

A technique to design the framework of removable partial denture by multi-stage expert system / 华西口腔医学杂志

This study aims to apply a new expert system to design removable partial denture (RPD) framework. The RPD design is completed in three steps, namely, "selecting missing teeth", "selecting abutment condition", and "selecting personalized clasp". The system can help auxiliary dentists develop personalized treatment plans to reduce their clinical workload. It can also generate a dental preparation guideline for clinical preparation, which can prevent tooth preparation mistakes. By generating the standard electronic drawings of the framework design, the system can reduce the inconvenience caused by manual drawing, thereby facilitating dentist-technician communication and reducing the rate of remade.

Advances in the application of machine learning in maxillofacial cysts and tumors / 华西口腔医学杂志

The application of artificial intelligence in medicine has gradually received attention along with its development. Many studies have shown that machine learning has a wide range of applications in stomatology, especially in the clinical diagnosis and treatment of maxillofacial cysts and tumors. This article reviews the application of machine learning in maxillofacial cyst and tumor to provide a new method for the diagnosis of oral and maxillofacial diseases.

Development and application of a system based on artificial intelligence for transcatheter aortic prosthesis selection

Abstract Introduction: The interest in Expert systems has increased in the medical area. Some of them are employed even for diagnosis. With the variability of transcatheter prostheses, the most appropriate choice can be complex. This scenario reveals an enabling environment for the use of an Expert system. The goal of the study was to develop an Expert system based on artificial intelligence for supporting the transcatheter aortic prosthesis selection. Methods: The system was developed on Expert SINTA. The rules were created according to anatomical parameters indicated by the manufacturing company. Annular aortic diameter, aortic area, aortic perimeter, ascending aorta diameter and Valsalva sinus diameter were considered. After performing system accuracy tests, it was applied in a retrospective cohort of 22 patients with submitted to the CoreValve prosthesis implantation. Then, the system indications were compared to the real heart team decisions. Results: For 10 (45.4%) of the 22 patients there was no concordance between the Expert system and the heart team. In all cases with discordance, the software was right in the indication. Then, the patients were stratified in two groups (same indication vs. divergent indication). The baseline characteristics did not show any significant difference. Mortality, stroke, acute myocardial infarction, atrial fibrillation, atrioventricular block, aortic regurgitation and prosthesis leak did not present differences. Therefore, the maximum aortic gradient in the post-procedure period was higher in the Divergent Indication group (23.9 mmHg vs. 11.9 mmHg, P=0.03), and the mean aortic gradient showed a similar trend. Conclusion: The utilization of the Expert system was accurate, showing good potential in the support of medical decision. Patients with divergent indication presented high post-procedure aortic gradients and, even without clinical repercussion, these parameters, when elevated, can lead to early prosthesis dysfunction and the necessity of reoperation.

Preparation of flavonoids from Glycyrrhiza uralensis by two-dimensional reversed-phase liquid chromatography / 中草药

Objective To develop a systematic chromatography separation method for flavonoids from Glycyrrhiza uralensis Fisch. (GU). Methods A new method for the separation of effective parts and monomers of flavonoids from GU by two-dimensional reversed-phase liquid chromatography was developed using the self-developed preparation chromatography plant system with independent intellectual property rights. Flavonoids compounds were enriched with specific adsorption materials. The separation conditions of the chromatography were optimized by the chromatographic separation expert system software, and the loading weight of samples and the enrichment times of a separation were investigated. Results The process of chromatography separation of flavonoids from GU had good precision and reproducibility with C18 as separation and enrichment solid phase and the methanol/water and acetonitrile/water as mobile phase of one-dimensional and two-dimensional chromatography system. The dilution solution which used for one-dimensional and two-dimensional enrichment chromatography was water. The flow rate of gradient elution and dilution enrichment solution was 21 mL/min. The sample loading amount of chromatography separation was 300 mg each time. A total of 16 flavonoids parts contained stable chemical composition were obtained by the repeatable separation method after three times of enrichment. Nine pure compounds were obtained and identified by NMR and MS, which were liquiritin, liquiritigenin, formononetin, echinatin, 7,4'-dihydroxyflavone, 4'-O-[β-D-apio-D-furanosyl-(1→2)-β-D-glucopyranosyl] liquiritigenin, isoliquiritigenin, glycyrol, and glycycoumarin. Conclusion The study can provide a certain reference value for the systematic separation and cognition for flavonoids from GU.

Application of artificial intelligence in diagnosis of diabetes / 中国医学装备

To analyze the application and research direction of artificial intelligence in the diagnosis field of diabetes through summarized the methods and principle of artificial intelligence, artificial neural network, expert system and data mining. The diagnosis of diabetes need be supported by large medical resource. The artificial intelligence is applied in the diagnosis of diabetes not only can save medical resource but also can help patients with diabetes and high risk group of diabetes to grasp their state of illness in time, and reduce the sickening risk of diabetic complication.

Discussion on the Problems of Vitek 2 Compact Advanced Expert System to Identify Carbapenemase Phenotypes in Isolates of Enterobacteriaceae / 现代检验医学杂志

Objective To explore the accuracy of Vitek 2 compact advanced expert system (AES) in indicating and analyze the carbapenemases-resisting Enterobacteriaceae phenotypes,and further investigate the methods to make up the AES.Methods 28 Enterobacteriaceae strains with Imipenem-Nonsusceptible by Vitek 2 compact,but AES suggested all production of carbapenemases were isolated.And imipenem susceptibility was determined by the disk diffusion method.Modified Hodge test (MHT) and the metallo-β-1actamase was detected by the double disk synergy method.Resistance genes were detected by the PCR amplification.Results ESBLs gene was amplified from all 28 selected strains,16 of which was detected KPC gene,and no strain of metallo-β-1actamases-producing bacteria.With carbapenemase gene detection as the gold standard,the accuracy of AES was 57.1％.Disc diffusion method detection accuracy rate of imipenem was 100％,and for 100％ of MHT accuracy.PCR amplification,MHT and the disk diffusion displayed the same result in detecting carbapenemases,but different with AES (x2 =10.08,P＜0.05).Conclusion The indications of the presence of carbapenemases using AES was not completely correct with a certain false-positive,and it is necessary to take other methods,such as disk diffusion or MHT methods,and improve the reliability of medicine-sensitivity tests.

Evaluation on the performance of MicroScan WalkAway in detecting carbapenem-resistant Enterobacteriaceae / 中国感染与化疗杂志

Objective To investigate the performance of MicroScan WalkAway 96 Plus (MSW) system in detection of carbapenem-resistant Enterobacteriaceae (CRE).Methods A total of 81 stock CRE strains were used in this study. Bacterial identification and antimicrobial susceptibility test were performed by MSW system. Beta-lactamases genes blaKPC,blaIMP,blaVIM, blaOXA-48 and blaNDM were amplified by PCR and subjected to sequencing analysis. Disk diffusion method and PCR were used as gold standard to evaluate the performance and reliability of MSW system in identifying carbapenem-resistant and carbapenemase-producing Enterobacteriaceae.Results Overall, 69.1 % (56/81) of the Enterobacteriaceae strains were identified as CRE by the MSW system. The results of PCR showed that 48 strains were carbapenemase-producing Enterobacteriaceae. When carbapenemase-producing Enterobacteriaceae strains were identified by the instrument using an advanced expert system, the sensitivity was 93.8 % and specificity was 42.4 %. The positive predictive value was 70.3 %, the negative predictive value was 82.4 % and the predictive accuracy value was 72.8 %.Conclusions The MicroScan WalkAway 96 Plus system has shown good performance in detection of CRE.

Performance and reliability of VITEK 2-Compact GN13 method and its Advanced Expert System validation for testing imipenem susceptibility of Klebsiella pneumoniae / 中国感染与化疗杂志

Objective To evaluate the performance of VITEK 2-Compact GN13 methods for testing imipenem susceptibility of Klebsiella pneumoniae and assess the reliability of its Advanced Expert System (AES).Methods A retrospective study was conducted with a total of 157K. pneumoniae strains, which were isolated from blood and intra-abdominal infections in the First Affiliated Hospital of Nanchang University from 2014 to 2015. Thein vitro minimum inhibitory concentration (MIC) values of imipenem were determined by disc diffusion, VITEK 2-Compact GN13 and broth microdilution methods, respectively. Categorical agreement (CA) rates of disc diffusion and VITEK 2-Compact GN13 methods were determined using broth microdilution as reference method. The genes encoding ESBLs and carbapenemase were screened by PCR and sequencing analysis. The phenotypic confirmatory tests such as modified Hodge test, PCR and DNA sequencing were used to confirm the resistance mechanism and evaluate the reliability of AES in interpreting the imipenem susceptibility of K. pneumoniae.Results Among the 157 isolates, 64 and 8 were identified as resistant and intermediate strains by broth microdilution method, respectively; 52 and 10 were tested as resistant and intermediate strains by disc diffusion method, respectively; 54 and 13 were determined as resistant and intermediate strains by VITEK 2-Compact GN13 method, respectively, while 70 and 3 were judged as resistant and intermediate strains by VITEK 2-Compact GN13 method plus AES validation. The CA of disc diffusion and VITEK 2-Compact GN13 methods compared with broth microdilution method were all higher than 90 %. However, the major error (ME) rate was 3.8 % and very major error (VME) rates were all 0.6 % in imipenem susceptibility testing by VITEK 2-Compact GN13 and disc diffusion. The imipenem susceptibility of 16 strains were modified by the AES, which eliminated 0.6 % VME, but increased major error by 1.3 % and minor error by 1.9 %. Phenotypic confirmatory tests showed that 75 % (12/16) of these strains were validated as producers of both ESBLs and carbapenemase, which was consistent with the result of AES validation. PCR and DNA sequencing analysis proved that 62.5 % (10/16) of these strains produce IMP-4/KPC-2 /NDM-1 and ESBLs.Conclusions Both disc diffusion and VITEK 2-Compact GN13 methods can be used for testing the imipenem susceptibility of K. pneumoniae isolates with reliable and accurate results. Attention should be paid to the possibility of ME and VME when testing imipenem susceptibility. The VME can be avoided by the AES mechanism. However, AES intervention will increase ME and minor error, which may be associated with decreased expression of carbapenemase.

Sistema experto para determinar la frecuencia cardiaca máxima en deportistas con factores de riesgo / Expert system for determining the heart rate maximum in athletes with risk factors / Sistema especialista para determinar a taxa coraçao maximo em atletas com fatores de risco

En este trabajo se presenta un sistema experto (SE) que permite establecer la frecuencia cardiaca máxima en términos de porcentaje de intensidad, la duración de una sesión de entrenamiento y la frecuencia en días por semana. La base del SE es el conocimiento de profesionales en el área de medicina y del deporte, que ayuda a los deportistas con padecimiento de enfermedades o factores de riesgo a tomar mejores decisiones al momento de realizar ejercicio físico. Este sistema se desarrolló en un ambiente web para facilitar la adquisición de los datos por parte de los profesionales, permitiendo así, la incorporación de varios criterios donde la aplicación del algoritmo del SE y de minería de datos proveen a los deportistas resultados con soporte médico. El SE ha sido incorporado a un software que se encarga de monitorizar la frecuencia cardiaca en tiempo real en una disciplina deportiva, donde se evidenció el buen funcionamiento del SE.

This paper presents an expert system (SE) that establishes the maximum heart rate in percentage terms of intensity, duration of a training session and frequency in days per week is presented. The base SE is the knowledge of professionals in the field of medicine and sport that helps athletes suffering from diseases or risk factors make better decisions at the time of exercise. This system was developed in a web environment to facilitate the acquisition of data by professionals, thus allowing the incorporation of several criteria where application of the algorithm SE and mining provide athletes results with medical support. The SE has been incorporated into software that is responsible for monitoring the heart rate in real time in a sport where the proper functioning of the SE was evident.

Este trabalho apresenta um sistema especialista (SE), que estabelece a frequência cardíaca máxima em termos percentuais de intensidade, a duração de uma sessão de treinamento ea freqüência em dias por semana é apresentado. A base de SE é o conhecimento de profissionais no campo da medicina e esporte, que ajuda atletas que sofrem de doenças ou factores de risco a tomar melhores decisões no momento do exercício. Este sistema foi desenvolvido em um ambiente web para facilitar a aquisição de dados por profissionais, permitindo a incorporação de vários critérios, quando a aplicação do algoritmo SE e mineração oferecer aos atletas resultados com apoio médico. A SE foi incorporado no software que é responsável por monitorar o ritmo cardíaco em tempo real em um esporte onde o bom funcionamento da SE foi evidente.

Uso da inteligência articial como armamento no diagnóstico e condução clínica da estenose de canal lombar / Use of Articial Intelligence in Diagnosis and Clinical Conduct of Lumbar Spinal Stenosis

A estenose do canal vertebral lombar (ECL) é uma patologia complexa, com alta incidência entre pessoas acima de 65 anos de idade. No entanto, o diagnóstico correto é, por vezes, difícil de ser confirmado. O uso de modelos de Inteligência Articial (IA) na medicina é, em geral, desconhecida para a maioria da comunidade médica, mas tem sido usada há décadas na assistência em UTI, os métodos de imagem e dispositivos de diagnóstico eletrônico (ECG). Através de uma revisão sistemática da literatura, com foco nos achados clínicos e radiológicos, juntamente com todas as modalidades de tratamento, foi possível identicar o ambiente completo de pacientes LSS, para responder a quatro questões: (a) "Com base no quadro clínico, o paciente tem um, cenário moderado ou grave?"; (b) "Com base nos dados radiológicos, o paciente pode ser classicado com um cenário leve,moderada ou grave?"; (c) "Qual é a probabilidade, com base na anamnese, do paciente ter ECL?"; (d) "Qual é o melhor tratamento a ser oferecido?".þ. Como auxílio de um software usando Sistema Especialista (Expert Sinta), uma linguagem de IA, alocamos todas as variáveis e seus valores para orientar o software responder às quatro perguntas. Foi possível identicar 657 artigos cientícos, no entanto apenas 63 poderia mencionar não apenas as variáveis, mas a sua probabilidade de ocorrência ou teve disponibilidade texto completo. Foi possível classicar a intensidade do quadro clínico e radiológico, criar um índice de probabilidade para LSS e oferecer o melhor tratamento. Recomendamos o uso, sob supervisão médica, em de Neurocirurgia ou clínicas ortopédicas como um conselheiro para os pacientes com ELA.

The lumbar spinal stenosis (LSS) is a complex pathology with high incidence among people above 65 years old. However, the correct diagnose is sometimes difcult to perform. The use of Articial Intelligence (AI) models in medicine is, in general, unfamiliar for the majority of medical community, but has been used for decades in assistance in ICUs, image methods and electronic diagnostic devices (EKG). Through a systematic literature review focused in the clinical and radiological ndings, in addition to all treatmentmodalities, we identied the complete environment of LSS patients, to answer four questions. (a) "Based on the clinical presentation, the patient has a mild, moderate or severe scenario?", (b) "Based on the radiological data, the patient can be classied having a mild, moderate or severe scenario?", (c) "What is the probability, based on the anamneses, the patient has LSS?", and (d) "What is the best treatment to be offered?".With the aid of a software using Expert System (Expert Sinta), a language of AI, we allocate all the variables and their values to orient the software to answer the four questions. It was possible to identify 657 scientic articles, however only 63 could mention not only the variables, but their occurrence probability or had full text availability. It was possible to classify the intensity the clinical and radiological scenario, create a probability index for LSS and offer the best treatment. We recommend the use, under medical supervision, in neurosurgery or orthopedic clinics as an adviser for patients with LSS.

The application of auxiliary diagnosis expert system of biochemical analyzer / 中国医学装备

The combination of biochemistry analyzer and medical expert system was proposed in this report. Biochemistry analyzer is one of the most important analytical instrument used in clinical detection. It could take immunological examination and biochemical analysis for blood, urine, pleural effusion and cerebrospinal fluid and other body fluids. Medical expert system is an intelligent program system with knowledge and experience of a large number of medical specialists. It could use the knowledge and method of medical experts to solve and deal with problems in the field. This system mainly includes human interface, inference engine, interpreter, knowledge acquisition procedures, integrated database and knowledge base. Some parts of system design, such as the expression and design, and interpretation mechanism of the knowledge base, have been interpreted in details. It adopts production as an expression of knowledge. Generally, knowledge was expressed as if the conditions, then the conclusion form. Interpretation mechanism use the error counter propagation of neural network to train the algorithm (BP algorithm for short).The combination could automatically conduct comprehensive analysis of various data generated by the instruments, and then obtain the science theoretical foundation and the most reasonable specialist conclusions. This report provides an overview of the system design of medical expert system.

Construction and application of clinical microbiology laboratory data management expert system / 中华临床感染病杂志

Objective To introduce the construction and application of clinical microbiology laboratory data management expert system.Methods Firstly, the process management was introduced to clinical microbiology laboratory. Then the characteristics of data on each node of work process were analyzed, and SQL Server data table was created as the knowledge base of the expert system.Finally, VB6.0 was used to compile the knowledge acquisition module, reasoning desktop module and input/output interface procedures to finally construct the expert system.Rates of defect report, errors in bacterial identification and drug sensitivity test, delay in culture results reporting and average delayed days were compared before and after the application of the expert system.Results The expert system could be used for data management in process nodes like sample reception, information collection and input, bacteria culture medium selection, bacterial identification and drug sensitive test, interpretation of drug sensitivity results, comprehensive evaluation in bacterial identification and drug sensitivity results, report of negative result, report of positive result, blood culture, Mycoplasma culture, time limit of detection, and nosocomial infection indicators.No defect report was found after the application of expert system; rate of errors in selection of drug sensitivity test medium was reduced from 0.81% ( 31/3 836 ) in 2012 to 0.02%(1/5 433) in 2014;rate of delay in culture results reporting was reduced from 1.78% (320/17 983) to 1.18%(232/19 692), and the average delayed days was also reduced (3.8 d vs.3.2 d).Conclusion Clinical microbiology laboratory data management expert system can improve work efficiency and reduce errors, which can enhance the overall management of laboratory and the quality of clinical service.

Application and Thinking of Computer Technology in the Field of Traditional Chinese Medicine / 中国中医药信息杂志

Computer technology is one of the greatest achievements of the 20th Century. Its appearance not only brings a breakthrough development in various fields, but also brings promotion to the development of traditional Chinese medicine (TCM). TCM is a traditional medicine, and the modernization of TCM is urgent. Whether in the medical management or scientific research, the application of computer technology has penetrated into all levels. The following article described the contribution made by computer technology, pointed out possible problems and provided relevant thinking based on the application of TCM related systems and data mining technology.

Sedea: Prototipo de sistema experto para el diagnóstico de enfermedades autoinmunes de órgano basado en internist / Sedea: Prototype expert system for the diagnosis of autoimmune diseases organ based internist

Realizar un buen diagnóstico es vital para el éxito en el tratamiento de una enfermedad, por ello, las herramientas que apoyan el proceso de diagnóstico son de gran interés. Particularmente, los especialistas en inmunología no cuentan con herramientas que apoyen el diagnóstico de enfermedades autoinmunes específicas de órgano. Esto hace que en dicho proceso los especialistas deban acudir a su experiencia y al conocimiento formalizado de esta área de la medicina. Pero cuando dicho conocimiento no está a la mano o simplemente no se cuenta con la experiencia, el diagnóstico presenta complicaciones que seguramente repercutirán en la salud del paciente. Desde las TI se han realizado diferentes intentos por colaborar en la tarea de diagnóstico, generalmente con la construcción de Sistemas Expertos que modelan el conocimiento de los especialistas ante circunstancias determinadas. Este trabajo plantea la creación de un prototipo de Sistema Experto para el Diagnóstico de Enfermedades Autoinmunes específicas de órgano SEDEA, el cual integra el conocimiento clínico con el modelo descriptivo ofrecido por Internist, a través de una ontología que permite manejar los diferentes conceptos por medio de reglas declaradas en el motor de inferencia de JESS, ofreciendo además interfaces que permiten ingresar y procesar datos con facilidad.

To make a good diagnosis is vital to the successful in the treatment of a disease. Therefore, tools that contribute to more accurate diagnosis are of great interest. Particularly, immunology specialists do not have tools to support the organ-specific autoimmune diseases diagnosis process. This makes that during this process, specialists must resort to their experience and to the formalized knowledge of this medicine area. But when the knowledge is not at hand or simply no one has the experience, the diagnosis presents complications which will surely impact on the patient’s health. Different efforts to collaborate in diagnostic task has been made from the IT field; generally in the building of Experts Systems that model the specialist knowledge to certain conditions. This paper proposes the creation of an Expert System prototype for the Diagnostic of organ-specific Autoimmune diseases SEDEA, which not only integrates the clinical knowledge with the Internist descriptive model through an ontology that allows to handle the different concepts using rules declared in the JESS inference engine, but alsomoffers interfaces toeasilyinsert and process data.

Expert support system for occupational therapist in the identification of sensory profile / Sistema especialista para apoiar o terapeuta ocupacional na identificação do perfil sensorial

Introduction Based on the increasing usability of technology in healthcare, this paper discusses the use of an expert system (ES) to identify the sensory profile of patients starting Occupational Therapy, allowing the professional to make assertive decisions in establishing priorities in the therapeutic plan.Objective To develop a decision support system from the Infant/Toddler Sensory Profile.Method Structuring of an ES based on Infant/Toddler Sensory Profile, from terms translation into Portuguese, identification of variables and domain values involved, and construction of production rules.Results Twelve variables were registered for the construction of the ES, 6 of these were treated as goal-variables, 20 rules being built.Conclusion This ES is an important support to the occupational therapist in the decision-making process of treatment plans, determining priorities and respecting the sensory profile of each child. In addition, it must be noted that there is no equivalent system.

Introdução Com a crescente usabilidade da tecnologia na área da saúde, este artigo aborda a utilização de um sistema especialista (SE) para identificar o perfil sensorial de pacientes a iniciarem o tratamento de Terapia Ocupacional, permitindo ao profissional tomar decisões assertivas no estabelecimento de prioridades no plano terapêutico.Objetivo Construir um sistema de apoio à decisão a partir do Infant/Toddler Sensory Profile.Método Estruturação de um SE baseado no Infant/Toddler Sensory Profile, a partir da tradução para o português dos termos contidos neste instrumento, identificação das variáveis e valores de domínio envolvidos; e a construção das respectivas regras de produção.Resultados Para a construção do SE foram cadastradas 12 variáveis, destas 6 foram tratadas como variáveis-objetivo, sendo construídas 20 regras.Conclusão O SE construído constitui apoio importante ao terapeuta ocupacional no processo de tomada de decisão sobre o plano terapêutico, determinando as prioridades e respeitando o perfil sensorial de cada criança. Além disso, é preciso salientar que não há um sistema equivalente.

Design of fuzzy expert system for diagnosis of cardiac diseases .

Background: The logical thinking of medical practitioners play significant role in decision making about diagnosis. It exhibits variation in decisions because of their approaches to deal with uncertainties and vagueness in the knowledge and information. Fuzzy logic has proved to be the remarkable tool for building intelligent decision making systems for approximate reasoning that can appropriately handle both the uncertainty and imprecision. Aims & Objective: To develop a generic fuzzy expert system framework that can be used to design specific fuzzy expert systems for particular medical domain. Material and Methods: The generic fuzzy expert system has been designed for diagnosis of cardiac diseases. The interface between visual basic and MatLab is powerful feature of the system that offers user friendly graphical user interface. Results: Need to arrive at the most accurate medical diagnosis in a timely manner is the main outcome that may reduce the further complications. A generic fuzzy expert system for the diagnosis of various heart diseases yields better result than the classic designed systems, because this system simulates the manner of an expert in true sense. Conclusion: The particular focus is on diagnosis of heart disease by employing the fuzzy logic in expert systems. The system has been designed and tested successfully. Exhaustive rule base specifically formed for almost all heart diseases ensures the accuracy to arrive at certain decision.

A fuzzy system for cloacal temperature prediction of broiler chickens / Sistema fuzzy para a predição da temperatura cloacal de frangos de corte

Cloacal temperature (CT) of broiler chickens is an important parameter to classify its comfort status; therefore its prediction can be used as decision support to turn on acclimatization systems. The aim of this research was to develop and validate a system using the fuzzy set theory for CT prediction of broiler chickens. The fuzzy system was developed based on three input variables: air temperature (T), relative humidity (RH) and air velocity (V). The output variable was the CT. The fuzzy inference system was performed via Mamdani's method which consisted in 48 rules. The defuzzification was done using center of gravity method. The fuzzy system was developed using MAPLE® 8. Experimental results, used for validation, showed that the average standard deviation between simulated and measured values of CT was 0.13°C. The proposed fuzzy system was found to satisfactorily predict CT based on climatic variables. Thus, it could be used as a decision support system on broiler chicken growth.

A temperatura cloacal (TC) de frangos de corte é um importante parâmetro para classificar a sua condição de conforto, portanto, a sua predição pode ser usada no suporte à decisão de acionamento de sistemas de climatização. Objetivou-se com a presente pesquisa desenvolver e validar um sistema, utilizando a teoria dos conjuntos fuzzy para predição da TC de frangos de corte. O sistema fuzzy foi desenvolvido com base em três variáveis de entrada: temperatura do ar (T), umidade relativa (UR) e velocidade do ar (V), tendo, como variável de saída, a TC. A inferência fuzzy foi realizada por meio do método tipo Mamdani, que consistiu na elaboração de 48 regras e a defuzzificação por meio do método do Centro de Gravidade. O sistema fuzzy foi desenvolvido no ambiente computacional MAPLE® 8. Resultados experimentais, usados para a validação, mostraram que o desvio padrão médio entre os valores simulados e medidos de TC foi de 0,13°C. O sistema fuzzy proposto prediz satisfatoriamente a TC com base nas variáveis climáticas, podendo ser utilizado como suporte à decisão em sistemas de criação de frangos de corte.