Sedan oktober 2011 sköter Sjukvårdens Larmcentral, SvLC, utalarmeringen av akuta sjukdomsfall som inkommer vid 112-samtal. Samtidigt infördes ett nytt medicinskt beslutsstöd för de sjuksköterskor som tar emot de akuta samtalen. Då orsaken till buksmärta är komplext och svårt att identifiera hos patienterna valdes just detta tillstånd för granskning. Syfte: Att undersöka om det medicinska beslutsstödet för sjuksköterskorna på SvLC i Uppsala län är en tillförlitlig hjälp i identifieringen av patienter med akuta buksmärtor, samt att undersöka om det fanns ålder-eller könsskillnader. Metod: En empirisk kvantitativ studie med en retrospektiv journalgranskning. Sammanlagt 151 patienter som ringt ambulans på grund av buksmärta och som av larmcentralen prioriterats som livshotande (prioritet 1) eller brådskande (prioritet 2) har granskats. Resultat: SvLC´s initiala bedömningar stämde väl överens med de prehospitala bedömningar sjuksköterskan i ambulans gjorde. Hos prio1-gruppen hade 48 % diagnostiserats buksmärta UNS, det vill säga buksmärta utan närmare specifikation, och hos prio 2-gruppen var det 40 % som fått samma diagnos. I denna undersökning kunde inga allvarliga brister identifieras i det nya medicinska beslutssystemet gällande akuta buksmärtor i Uppsala län, och inga signifikanta ålder-eller könsskillnader kunde hittas. Mer studier skulle behövas för att öka träffsäkerheten gällande resultatet i detta ämne och fler patienter skulle behöva involveras för att ”fånga upp” eventuella brister i detta medicinska beslutssystem. / Since October 2011 Sjukvårdens Larmcentral (SvLC) take care of emergency calls. At the same time new decision support tool for nurses that receive the emergency calls was introduced, andit was of interest to find out if there are flaws in the emergency call- system. Since the cause of abdominal pain in patients is a complex and difficult to identify this specific condition was chosen for this study. Aim: To examine whether the new medical decision support for patients with acute abdominal pain after the introduction of the new medical decision- making aid is a reliable working aid. Method: An empirical quantitative study with retrospective review of patients records. Totally 151 patients who called ambulance due to abdominal pain and that the emergency call- center prioritized as life-threatening (priority 1) or urgent (priority 2) has been reviewed. Result: SvLC´s initial evaluation tallied well with the prehospital assessment the nurse in ambulance did. In the prio 1-group 48% diagnosed abdominal pain NOS, that is to say “Not Otherwise Specified”, and in prio 2 group 40% received the same diagnosis. In this investigation, no serious flaws identified in the new medical decision support regarding acute abdominal pain in Uppsala county, and no significant..... More studies would be needed to increase accuracy on the results in this topic and more patients would need to be involved in order to “capture” any deficiencies in this medical decision systems.

Στην παρούσα διπλωματική εργασία παρουσιάζονται τα ιατρικά συστήματα λήψης απόφασης (MDSS) και αρχιτεκτονικές ανάπτυξή τους. Πραγματεύεται τις έννοιες του ευφυούς ελέγχου και της ασάφειας για να καταλήξει στον όρο Ασαφή Γνωστικά Δίκτυα(FCΜ). Αφού περιγράφεται αναλυτικά η ανάπτυξή, ο καθορισμός των παραμέτρων και οι μεθοδολογίες εκμάθησης ενός Ασαφούς Γνωστικού Δικτύου, καταλήγει τελικά στην εφαρμογή τους στον χώρο της ιατρικής. Τέλος, ακολουθεί το μοντέλο ενός Ασαφούς Ελεγκτή για ιατρικές εφαρμογές και η ανάπτυξη ενός MDSS για την εύρεση Κάκωσης Γόνατος με αρχιτεκτονικές Ανταγωνιστικού Ασαφούς Γνωστικού Δικτύου (CFCΜ). / The thesis represents the medical decision support systems (MDSS) and their architecture. Starting with the concepts of intelligent control and Fuzzy Cognitive Maps (FCM), it describes in detail the development, the setting parameters, and the learning methods of FCMs, with the purpose of their application into the field of medicine. Finally, it illustrates the model of a Fuzzy Controller for medical applications and the development of an MDSS for finding knee injury with the architecture of Competitive FCMs (CFCM).

No description available.

Submitted by Maria Anália Conceição (marianaliaconceicao@gmail.com) on 2016-08-18T18:29:46Z No. of bitstreams: 1 Publico-10.pdf: 2044084 bytes, checksum: eef64e9d622b35c3b0880540380f1814 (MD5) / Approved for entry into archive by Maria Anália Conceição (marianaliaconceicao@gmail.com) on 2016-08-18T18:31:35Z (GMT) No. of bitstreams: 1 Publico-10.pdf: 2044084 bytes, checksum: eef64e9d622b35c3b0880540380f1814 (MD5) / Made available in DSpace on 2016-08-18T18:31:35Z (GMT). No. of bitstreams: 1 Publico-10.pdf: 2044084 bytes, checksum: eef64e9d622b35c3b0880540380f1814 (MD5) Previous issue date: 2005 / Intel do Brasil / Altos índices de mortalidade infantil em comunidades carentes podem ser evitados através da identificação precoce dos fatores de risco e do acompanhamento direto e contínuo da assistência médica materno infantil. No entanto, essa assistência demonstra ser complexa, com precariedade na locomoção e troca de informação das equipes da saúde, comumente constituídas por profissionais de diversas especialidades. Ainda, verifica-se uma freqüente participa- ção de voluntários de organizações não governamentais envolvidos diretamente com essa assistência. O objetivo desse trabalho foi desenvolver um instrumento digital – aqui denominado Sistema BabyCare – para a coleta, armazenamento e apoio à decisão aos profissionais de saúde, e demais envolvidos, nos cuidados a pacientes na assistência primária infantil em comunidades carentes. Esse sistema baseia-se em tecnologias de dispositivos móveis para utilização local em unidades básicas de saúde em comunidades carentes, assistidos ou não pelo Programa Saúde da Família (PSF), e ambulatórios e hospitais. Foram realizadas avaliações sobre o uso do sistema na cidade de São Paulo, envolvendo 60 usuários com diferentes formações, incluindo voluntários da Pastoral da Criança. Os questionários aplicados resultam um alto índice de aceitação geral (98,3%); treinamento in loco considerado adequado (91,9%); percepção na melhoria na rotina e na redução de tempo da consulta (100,0%), e na redução no volume de documentos (96,7%). Por fim, o protótipo apresentou-se robusto e eficiente para uso em comunidade / High infant mortality rates in needy communities can be prevented through direct and continuous follow-up of maternal and child health care. However, this assistance has proven to be complex, with the precarious mobility and exchange of information of healthcare teams, usually consisting of professionals from different specialties. In addition, there is a frequent participation of volunteers from non-governmental organizations directly involved in this assistance. The purpose of this work was to develop a digital device – referred as BabyCare System – for the collection, storage and support to decision for healthcare professionals and other concerned people, in order to assist patients in primary child care in needy communities. This system is based on handheld device technologies to be used locally in basic healthcare units in needy communities, whether assisted or not by the Healthcare Family Program (Programa Saúde da Família – PSF), as well as in ambulatory facilities and hospitals. Evaluations have been conducted regarding the use of the system in the city of São Paulo, involving 60 users with different formations, including volunteers from the Pastoral da Criança, an ecumenical institution for children. The applied questionnaires result in a high level of general acceptance (98.3%); the on-site training was considered as appropriate (91.9%); a perception of routine improvement and decrease in the time of consultation (100.0%), and a decrease in the volume of paperwork (96.7%). Finally, the prototype has proven to be robust and effective for the use in needy communities with precarious computer and telecommunication infrastructure.

Submitted by Frederico Azevedo (fazevedo@cdts.fiocruz.br) on 2010-11-10T17:01:50Z No. of bitstreams: 1 oliveiravsm.pdf: 1878124 bytes, checksum: 96c6fd44407809d315bca0121b1f16ff (MD5) / Made available in DSpace on 2010-11-10T17:01:50Z (GMT). No. of bitstreams: 1 oliveiravsm.pdf: 1878124 bytes, checksum: 96c6fd44407809d315bca0121b1f16ff (MD5) Previous issue date: 2005 / Este trabalho analisa as possibilidades de tornar interoperáveis bases de dados heterogêneas, de forma que possam ser pesquisadas através de uma única interface. A biblioteca do Instituto Fernandes Figueira, Unidade materno-infantil da FIOCRUZ é referência em tratamento de doenças de alta complexidade. Estes profissionais buscam a Biblioteca com necessidades de informações voltadas para a decisão clínica. As bases de dados mais pesquisadas por estes profissionais são as bases de dados LILACS, MEDLINE e ACERVOS ONLINE FIOCRUZ. Portanto estas bases norteiam este estudo e são analisadas em algumas facetas como: os procedimentos de descrição e as estruturas das bases, buscando semelhanças e divergências nos índices e nos campos de exibição das bases; a representação temática, caracterizada pela utilização dos Tesauros DeCS e MeSH; e tecnologias utilizadas e/ou compatíveis. Paralelamente busca-se apresentar algumas ferramentas tecnológicas atuais de interoperabilidade como os protocolos Z39.50 e o OAI-PMH, os metabuscadores, o conjunto de metadados Dublin Core e o MetaIAH. Através destas análises delineou-se três modelos conceituais para alcançar a interoperabilidade, são eles: Compartilhamento de Esforços, quando tanto a Interface de Consulta (IC) e os Recursos Informacionais (RI) trabalham para garantir a interoperabilidade; Esforço concentrado nos RIs, quando os Recursos Informacionais arcam com todo o esforço para possibilitar a interoperabilidade; e, Esforço concentrado na IC, quando a Interface de consulta se adapta para suprir as divergências de cada base proporcionando a interoperabilidade. Para finalizar comparam-se os modelos e as bases de dados estudadas destacando-se os modelos que se constituem como alternativas de interoperabilidade para a biblioteca do Instituto Fernandes e quais as vantagens e desvantagens de cada uma delas. / This work analyses the options to achieve interoperability among different library databases so they can be searched from a single Web interface. The databases object of this research are the ones used in The Fernandes Figueira Institute Library, which is a branch of FIOCRUZ specialized in Maternal and Child Health. Library users generally look for medical decision support information. The Library users preferred databases are LILACS, MEDLINE and ACERVOS ONLINE FIOCRUZ. All of them use the DeCS and MeSH Thesaurus to subject description. Each of these databases are analyzed in aspects as access points, bibliographic description and display formats, in order to identify common elements. Technologies and standards to achieve interoperability as Z39.50 and OAI-PMH protocols, meta-search engines, Dublin Core Metadata Set BIREME’s metaIaH meta-search engine are also analyzed. From this analysis emerged three conceptual models to achieve interoperability among the three databases, evolving two actors, the search interface – SI, and the information resources (the three databases) - IR: Effort Sharing, between SI and IRs; Concentrated Effort in the RIs; and Concentrated Effort in the SI to achieve interoperability. The three models are compared, outlining the advantages and disadvantages of each one to achieve interoperability, among the databases of interest to Fernandes Figueira Institute Library.

The goal of this master’s thesis is to identify and evaluate data mining algorithms which are commonly implemented in modern Medical Decision Support Systems (MDSS). They are used in various healthcare units all over the world. These institutions store large amounts of medical data. This data may contain relevant medical information hidden in various patterns buried among the records. Within the research several popular MDSS’s are analyzed in order to determine the most common data mining algorithms utilized by them. Three algorithms have been identified: Naïve Bayes, Multilayer Perceptron and C4.5. Prior to the very analyses the algorithms are calibrated. Several testing configurations are tested in order to determine the best setting for the algorithms. Afterwards, an ultimate comparison of the algorithms orders them with respect to their performance. The evaluation is based on a set of performance metrics. The analyses are conducted in WEKA on five UCI medical datasets: breast cancer, hepatitis, heart disease, dermatology disease, diabetes. The analyses have shown that it is very difficult to name a single data mining algorithm to be the most suitable for the medical data. The results gained for the algorithms were very similar. However, the final evaluation of the outcomes allowed singling out the Naïve Bayes to be the best classifier for the given domain. It was followed by the Multilayer Perceptron and the C4.5.

No description available.

Made available in DSpace on 2015-05-14T12:36:36Z (GMT). No. of bitstreams: 1 ArquivoTotalRenata.pdf: 2638998 bytes, checksum: c2e2373b63cd157ac4705018a4e58468 (MD5) Previous issue date: 2013-02-19 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / In recent years, there was an increasing interest in the use of information technology in the medical field. In this way, several studies have been conducted regarding a large range of diseases, including cancer. For example, there are organizations that maintain databases, which record information about cases of cancer around the world, so that health personnel can investigate such bases and find possible classifications for an initial diagnostic according to the symptoms presented by their patients. However, these databases do not offer a proper support for this investigation. This dissertation discusses the use of the of case-based reasoning and rule-based reasoning technologies as a solution to support medical diagnosis via representations of actual patients and adaptations of these cases to define more specialized diagnoses, according to the peculiarities of each patient. The data collection was carried out in the Napoleao Laureano Hospital, at Joao Pessoa city, and the information inherent in the structure of the case, the rules and weights were defined in accordance with the specialized literature and conversations with health professionals. Despite the absence of a specialist, the small base of cases and presence of limited information on each of them, the results showed that the system is effective as a RBC system aimed at diagnosis about cancer. The focus of this project is on the main gastrointestinal cancer domain, but the ideas can be extended to other fields of cancer. / O tratamento de pacientes com câncer é um desafio para os hospitais e centros de saúde. O primeiro problema é classificar ou identificar o tipo específico de câncer. Em seguida, os médicos devem determinar um tratamento adequado para tal doença. Existem bancos de dados mundiais que registram informações sobre câncer, de modo que os médicos possam tentar achar uma classificação para a doença de acordo com os sintomas apresentados pelo paciente. Contudo eles não oferecem um bom suporte para a procura das doenças e, principalmente, para a identificação do tratamento. Este artigo propõe a utilização das tecnologias de raciocínio baseado em casos e raciocínio baseado em regras como solução para suportar estas duas atividades via representações de casos de pacientes e adaptações destes casos para a definição de diagnósticos mais especializados, de acordo com as peculiaridades de cada paciente. Nosso foco é sobre o câncer gastrointestinal, mas as idéias podem ser estendidas para outros domínios de câncer.

Orientador: Luís Cuadrado Martin / Resumo: O conhecimento sobre qualquer patologia pode ser facilmente encontrado na internet, mas dificilmente encontra-se alguma ferramenta que faça a análise e o raciocínio entre os dados de um paciente e se obtenha o diagnóstico mais provável. Em nosso cotidiano, em virtude de uma maior demanda na área da saúde, existe uma necessidade crescente de diagnósticos médicos rápidos e precisos. Em virtude disso, foi elaborado um Sistema de Apoio à Decisão Médica com o intuito de otimizar e agilizar de forma confiável os diagnósticos médicos. A ideia é dar qualidade e agilidade à prática médica, adotando a tecnologia como ferramenta básica: “Quem tem mais informação, tem melhores condições para escolher e tomar decisões”. Na construção deste sistema, foram utilizados um banco de dados relacional (MySQL) e aplicadas técnicas de inteligência artificial, tais como: a construção de Árvores de Decisão, Aprendizado não supervisionado e a utilização das Redes de Bayes (onde estão envolvidos domínios de conhecimento com significativo grau de incerteza, como é o caso da área médica). Através da união destas técnicas, são feitas a seleção e classificação das doenças mais prováveis, onde as mesmas podem ser examinadas com mais detalhes pelo médico, garantindo assim uma maior segurança na escolha dos possíveis diagnósticos. Visando uma maior abrangência e rapidez na disseminação do conhecimento humano, o sistema foi disponibilizado via internet (www.danton.med.br). Para a concepção do projeto foi reali... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The knowledge about any pathology can be easily found on the internet, but it is difficult to find any tool that makes the analysis and reasoning between the data of a patient and obtain the most probable diagnosis. In our daily lives, due to a greater demand in the health area, there is a growing need for fast and accurate medical diagnoses. As a result, a Medical Decision Support System was developed in order to reliably optimize and streamline medical diagnostics. The idea is to give quality and agility to medical practice, adopting technology as a basic tool: “Who has more information, has better conditions to choose and make decisions”. In the construction of this system, a relational database (MySQL) was used and artificial intelligence techniques were applied, such as: the construction of Decision Trees, Unsupervised Learning and the use of Bayes Networks (where knowledge domains are involved with significant degree of uncertainty, as is the case in the medical field). Through the union of these techniques, the selection and classification of the most probable diseases are made, where they can be examined in more detail by the doctor, thus ensuring greater security in the choice of possible diagnoses. Aiming at a greater scope and speed in the dissemination of human knowledge, the system was made available via internet (www.danton.med.br). To design the project, a prospective, randomized, crossover and open study was carried out; in which 3 groups of doctors (called gr... (Complete abstract click electronic access below) / Doutor

No description available.