Medication is an essential part of health care and enables the prevention andtreatment of many conditions. However, medication errors and drug-relatedproblems (DRP) are frequent and cause suffering for patients and substantial costsfor society. eMedication, defined as information technology (IT) in themedication management process, has the potential to increase quality, efficiencyand safety but can also cause new problems and risks.In this thesis, we have studied the employment of IT in different steps of themedication management process with a focus on the user's perspective. Sweden isone of the leading countries when it comes to ePrescribing, i.e. prescriptionstransferred and stored electronically. We found that ePrescribing is well acceptedand appreciated by pharmacists (Study I) and patients (Study II), but that therewas a need for improvement in several aspects. When the pharmacy market inSweden was re-regulated, four new dispensing systems were developed andimplemented. Soon after the implementation, we found weaknesses related toreliability, functionality, and usability, which could affect patient safety (StudyIII). In the last decade, several county councils in Sweden have implementedshared medication lists within the respective region. We found that physiciansperceived that a regionally shared medication list generally was more complete butoften not accurate (Study IV). Electronic expert support (EES) is a decisionsupport system which analyses patients´ electronically-stored prescriptions in orderto detect potential DRP, i.e. drug-drug interactions, therapy duplication, highdose, and inappropriate drugs for geriatric or pediatric patients. We found thatEES detected potential DRP in most patients with multi-dose drug dispensing inSweden (Study V), and that the majority of alerts were regarded as clinicallyrelevant (Study VI).For an improved eMedication, we need a holistic approach that combinestechnology, users, and organization in implementation and evaluation. The thesissuggests a need for improved sharing of information and support for decisionmaking, coordination, and education, as well as clarification of responsibilitiesamong involved actors in order to employ appropriate IT. We suggestcollaborative strategic work and that the relevant authorities establish guidelinesand requirements for IT in the medication management process. / Läkemedel förbättrar och förlänger livet för många och utgör en väsentlig del av dagens hälso- och sjukvård men om läkemedel tas i fel dos eller kombineras felaktigt med varandra kan behandlingen leda till en försämrad livskvalitet, sjukhusinläggningar och dödsfall. En del av dessa problem skulle kunna förebyggas med rätt information till rätt person vid rätt tidpunkt och i rätt form. Informationsteknik i läkemedelsprocessen har potentialen att öka kvalitet, effektivitet och säkerhet genom att göra information tillgänglig och användbar men kan också innebära problem och risker. Det är dock en stor utmaning att i läkemedelsprocessen föra in effektiva och användbara IT-system som stödjer och inte stör personalen inom sjukvård och på apotek, skyddar den känsliga informationen för obehöriga och dessutom fungerar tillsammans med andra system. Dagens IT-stöd i läkemedelsprocessen är otillräckliga. Till exempel saknar läkare, farmaceuter och patienter ofta tillgång på fullständig och korrekt information om en patients aktuella läkemedel; det händer att fel läkemedel blir utskrivet eller expedierat på apotek; och bristande eller långsamma system skapar frustration hos användarna. Dessutom är det flera delar av läkemedelsprocessen som fortfarande är pappersbaserade. Därför är det viktigt att utvärdera IT-system i läkemedelsprocessen. Vi har studerat IT i olika delar av läkemedelsprocessen, före eller efter införandet, framför allt utifrån användarnas perspektiv. Sverige har lång erfarenhet och tillhör de ledande länderna i världen när det gäller eRecept, det vill säga recept som skickas och lagras elektroniskt. I två studier fann vi att eRecept är väl accepterat och uppskattat av farmaceuter (Studie I) och patienter (Studie II), men att det finns behov av förbättringar. När apoteksmarknaden omreglerades 2009 infördes fyra nya receptexpeditionssystem på apoteken. Vi fann att det efter införandet uppstod problem med användbarhet, tillförlitlighet och funktionalitet som kan ha inneburit en risk för patientsäkerheten (Studie III). I Sverige har man inom flera sjukvårdsregioner infört gemensamma elektroniska läkemedelslistor. I en av studierna kunde vi visa att detta har inneburit en ökad tillgänglighet av information, men att en gemensam lista inte alltid blir mer korrekt och kan innebära en ökad risk att känslig information nås av obehöriga (Studie IV). I två av studierna undersöktes beslutsstödssystemet elektroniskt expertstöd (EES):s potential som stöd för läkare att upptäcka läkemedelsrelaterade problem till exempel om en patient har två olika läkemedel som inte passar ihop, eller ett läkemedel som kanske är olämpligt för en äldre person. Studierna visade att EES gav signaler för potentiella problem hos de flesta patienter med dosdispenserade läkemedel i Sverige (Studie V), och läkarna ansåg att majoriteten av signalerna är kliniskt relevanta och att några av signalerna kan leda till förändringar i läkemedelsbehandlingen (Studie VI). Sammantaget visar avhandlingen att IT-stöd har blivit en naturlig och nödvändig del i läkemedelsprocessen i Sverige men att flera problem är olösta. Vi fann svagheter med användbarhet, tillförlitlighet och funktionalitet i de använda IT-systemen. Patienterna är inte tillräckligt informerade och delaktiga i sin läkemedelsbehandling. Läkare och farmaceuter saknar fullständig och korrekt information om patienters läkemedel, och de har i dagsläget inte tillräckliga beslutsstöd för att förebygga läkemedelsrelaterade problem. Eftersom läkemedelsprocessen är komplex med många aspekter som påverkar utfall behöver vi ett helhetstänkande när vi planerar, utvecklar, implementerar och utvärderar IT-lösningar där vi väger in både tekniska, sociala och organisatoriska aspekter. Avhandlingens resultat visar på ett behov av ökad koordination och utbildning samt förtydligande av ansvaret för inblandade aktörer. Vi föreslår gemensamt strategiskt arbete och att inblandade myndigheter tar fram vägledning och krav för IT i läkemedelsprocessen.

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With the help of appropriate IT support, health care services can be executed in a more effective and secure way. In Sweden, the NPÖ (National Patients’ Översikt) stands for National Patients’ Overview. It is a platform where authorized health care providers can access comprehensive and continuous information about health care and patients’ situation, based on which care providers can offer safe and qualified services. The NPÖ project is focusing on the information sharing phase. In order to improve the efficiency and correctness of care services, the next step is that health care systems can offer clinical suggestions and warnings with the existing patients’ data and medication information. Clinical Decision Support Systems (CDSSs) are aimed to offer such assistance and are necessary to be integrated. But by now, there is no explicit architecture to guide Swedish government to implement the integration. Although some architectures have been proposed for integrating CDSSs in health information systems, those architectures are developed for certain use cases and cannot be adopted directly in NPÖ. An integration architecture which takes full consideration of NPÖ-adopting data types, message structures and interface types is needed. This thesis adopts constructive research method, which contains three main phases. First, related backgrounds about national electronic health care system, clinical decision supports system and integration techniques are introduced. Second, the integration architecture is constructed following service-oriented principles. Third, theoretical valuation work is finished by assessing system features and making interviews. This thesis takes advantage of service-oriented architecture to design an architecture with Clinical Decision Support (CDS) middleware for health care information system integration. With this structure, national electronic health care systems, such as NPÖ, can have interaction with various types of CDSSs to provide more efficient and secure health care. It offers united interfaces which enable different CDSSs with different developing platforms to communicate without obstacles. Unlike the existing CDSS integration architectures, the new one with CDS Middleware can provide maximized scalability. Evaluation work has been done from two aspects. Feature criteria and interviews with national health care system developers indicate that the architecture can contribute to the development of NPÖ, and future works such as involving security agents can be continued to optimize the results.

Das Treffen komplexer medizinischer Entscheidungen wird durch die stetig steigende Menge an zu berücksichtigenden Informationen zunehmend komplexer. Dieser Umstand ist vor allem auf die Verfügbarkeit von immer präziseren diagnostischen Methoden zur Charakterisierung der Patienten zurückzuführen (z.B. genetische oder molekulare Faktoren). Hiermit einher geht die Entwicklung neuartiger Behandlungsstrategien und Wirkstoffe sowie die damit verbundenen Evidenzen aus klinischen Studien und Leitlinien. Dieser Umstand stellt die behandelnden Ärztinnen und Ärzte vor neuartige Herausforderungen im Hinblick auf die Berücksichtigung aller relevanten Faktoren im Kontext der klinischen Entscheidungsfindung. Moderne IT-Systeme können einen wesentlichen Beitrag leisten, um die klinischen Experten weitreichend zu unterstützen. Diese Assistenz reicht dabei von Anwendungen zur Vorverarbeitung von Daten für eine Reduktion der damit verbundenen Komplexität bis hin zur systemgestützten Evaluation aller notwendigen Patientendaten für eine therapeutischen Entscheidungsunterstützung. Möglich werden diese Funktionen durch die formale Abbildung von medizinischem Fachwissen in Form einer komplexen Wissensbasis, welche die kognitiven Prozesse im Entscheidungsprozess adaptiert. Entsprechend werden an den Prozess der IT-konformen Wissensabbildung erhöhte Anforderungen bezüglich der Validität und Signifikanz der enthaltenen Informationen gestellt. In den ersten beiden Kapiteln dieser Arbeit wurden zunächst wichtige methodische Grundlagen im Kontext der strukturierten Abbildung von Wissen sowie dessen Nutzung für die klinische Entscheidungsunterstützung erläutert. Hierbei wurden die inhaltlichen Kernthemen weiterhin im Rahmen eines State of the Art mit bestehenden Ansätzen abgeglichen, um den neuartigen Charakter der vorgestellten Lösungen herauszustellen. Als innovativer Kern wurde zunächst die Konzeption und Umsetzung eines neuartigen Ansatzes zur Fusion von fragmentierten Wissensbausteinen auf der formalen Grundlage von Bayes-Netzen vorgestellt. Hierfür wurde eine neuartige Datenstruktur unter Verwendung des JSON Graph Formats erarbeitet. Durch die Entwicklung von qualifizierten Methoden zum Umgang mit den formalen Kriterien eines Bayes-Netz wurden weiterhin Lösungen aufgezeigt, welche einen automatischen Fusionsprozess durch einen eigens hierfür entwickelten Algorithmus ermöglichen. Eine prototypische und funktionale Plattform zur strukturierten und assistierten Integration von Wissen sowie zur Erzeugung valider Bayes-Netze als Resultat der Fusion wurde unter Verwendung eines Blockchain Datenspeichers implementiert und in einer Nutzerstudie gemäß ISONORM 9241/110-S evaluiert. Aufbauend auf dieser technologischen Plattform wurden im Anschluss zwei eigenständige Entscheidungsunterstützungssysteme vorgestellt, welche relevante Anwendungsfälle im Kontext der HNO-Onkologie adressieren. Dies ist zum einen ein System zur personalisierten Bewertung von klinischen Laborwerten im Kontext einer Radiochemotherapie und zum anderen ein in Form eines Dashboard implementiertes Systems zur effektiveren Informationskommunikation innerhalb des Tumor Board. Beide Konzepte wurden hierbei zunächst im Rahmen einer initialen Nutzerstudie auf Relevanz geprüft, um eine nutzerzentrische Umsetzung zu gewährleisten. Aufgrund des zentralen Fokus dieser Arbeit auf den Bereich der klinischen Entscheidungsunterstützung, werden an zahlreichen Stellen sowohl kritische als auch optimistische Aspekte der damit verbundenen praktischen Lösungen diskutiert.:1 Introduction 1.1 Motivation and Clinical Setting 1.2 Objectives 1.3 Thesis Outline 2 State of the Art 2.1 Medical Knowledge Modeling 2.2 Knowledge Fusion 2.3 Clinical Decision Support Systems 2.4 Clinical Information Access 3 Fundamentals 3.1 Evidence-Based Medicine 3.1.1 Literature-Based Evidence 3.1.2 Practice-Based Evidence 3.1.3 Patient-Directed Evidence 3.2 Knowledge Representation Formats 3.2.1 Logic-Based Representation 3.2.2 Procedural Representation 3.2.3 Network or Graph-Based Representation 3.3 Knowledge-Based Clinical Decision Support 3.4 Conditional Probability and Bayesian Networks 3.5 Clinical Reasoning 3.5.1 Deterministic Reasoning 3.5.2 Probabilistic Reasoning 3.6 Knowledge Fusion of Bayesian Networks 4 Block-Based Collaborative Knowledge Modeling 4.1 Data Model 4.1.1 Belief Structure 4.1.2 Conditional Probabilities 4.1.3 Metadata 4.2 Constraint-Based Automatic Knowledge Fusion 4.2.1 Fusion of the Bayesian Network Structures 4.2.2 Fusion of the Conditional Probability Tables 4.3 Blockchain-Based Belief Storage and Retrieval 4.3.1 Blockchain Characteristics 4.3.2 Relevance for Belief Management 5 Selected CDS Applications for Clinical Practice 5.1 Distributed Knowledge Modeling Platform 5.1.1 Requirement Analysis 5.1.2 System Architecture 5.1.3 System Evaluation 5.1.4 Limitations of the Proposed Solution 5.2 Personalization of Laboratory Findings 5.2.1 Requirement Analysis 5.2.2 System Architecture 5.2.3 Limitations of the Proposed Solution 5.3 Dashboard for Collaborative Decision-Making in the Tumor Board 5.3.1 Requirement Analysis 5.3.2 System Architecture 5.3.3 Limitations of the Proposed Solution 6 Discussion 6.1 Goal Achievements 6.2 Contributions and Conclusion 7 Bibliography

Treatment decision-making in head and neck oncology is gaining complexity by the increasing evidence pointing towards more individualized and selective treatment options. Therefore, decision making in multidisciplinary teams is becoming the key point in the clinical pathways. Clinical decision-support systems based on Bayesian networks can support complex decision-making processes by providing mathematically correct and transparent advises. In the last three decades, different clinical applications of Bayesian networks have been proposed. Because appropriate data for model learning and testing is often unobtainable, expert modeling is required. To decrease the modeling and validation effort, networks usually represent small or highly simplified decision structures. However, especially systems for supporting multidisciplinary treatment decisions may only gain a user’s confidence if the systems’ results are comprehensive and comprehensible. Challenges in developing such systems relate to knowledge engineering, model validation, system interaction, clinical implementation and standardization. These challenges are well-known, however, they are not or only partially addressed by the developers. The thesis presented a methodology for the development of Bayesian network-based clinical treatment decision support systems. For this purpose, a concept introduced interactions between actors and systems. The proposed concept emphasizes model development with an exemplary use case of model interaction. A graph model design was presented that allows integrating all relevant variables of multidisciplinary treatment decisions. At the current stage, we developed TreLynCa: A graph model representing the treatment decisions of laryngeal cancer. From TreLynCa, a subnetwork that represents the TNM staging is completed by the required probabilistic parameters, and finally validated. The model validation required the development of a validation cycle in combination with existing data- and expert-based validation methods. Furthermore, modeling methods were developed that enable domain experts to model autonomously without Bayesian network expertise. Specifically, a novel graph modeling method was developed, and an existing method for modeling probabilistic parameters was extended. Both methods transform Bayesian network modeling tasks into a natural language form and provide a regulated modeling environment. A method for graph modeling is based on the presented graph model design with a regulated and restricted modeling procedure. This modeling procedure is supposed to enable collaborative modeling of compatible models. The method is currently under development. A method for probabilistic modeling is extended to reduce the modeling effort to a linear time. The method has been implemented as a web tool and was tested and evaluated in two studies. Finally, for clinical application of the TNM model, requirements were collected and constructed in a visual framework. In collaboration with visual scientists, the framework has been implemented and evaluated.

Purpose:The thesis will shed light on the overall need of CDSSs in the Swedish health care system,  and  it  will  also  present  a  specific  efficiency  problem  that  could  be  solved  by implementing a CDSS. The need for a CDSS is where an implementation would improve patient outcome, by delivering the right care at the right time, and where the CDSS could reduce the cost of the delivered care. A better understanding of the current need could help eliminate the existing empirical gap and ultimately lead to better and more efficient health care in Sweden. The research question was formulated as: Where within Swedish health care can a need for increased efficiency be met through the implementation of a realistic CDSS system? Design and methodology: The  thesis  is  a  case  study  where qualitative data, collected through a literature review and interviews, was used to answer the research question. The methodology used was tailored to the unique setting of the research and in accordance to the purpose of the study. The method was divided into five phases. (1) Finding an area of focus, such as a specific diagnosis, within the health care system where the need for a CDSS system is deemed high. (2) Mapping the care chain of the identified area of interest. (3) Developing hypotheses concerning where in the care chain challenges could be solved using a clinical decision support system. (4) Confirming or rejecting the proposed hypotheses through interviews with relevant experts. (5) Presenting the specific efficiency problem that could be solved using a CDSS and a presentation of the design of said CDSS. Findings: The efficiency problem that could be solved using a CDSS was identified to be within the area of heart failure treatment. There were a multitude of areas of improvement found along the care chain and a number of them could be solved by developing and using specific CDSSs. A CDSS that could help physicians, within the primary care system, to identify patients that  could benefit from  being  assessed  by  cardiology specialist was  proposed  as  the  most beneficial  CDSS  system.  The  proposed  CDSS  would  be  both  beneficial  and  realistically implementable. / Syftet med uppsatsen är att belysa det övergripande behovet av kliniska beslutsstödssystem inom den svenska vården och slutligen finna det mest trängande behovet. En bättre förståelse för detta behov kan hjälpa att minska det existerande empiriska gapet och slutligen leda till en bättre och mer effektiv vård i Sverige. Forskarfrågan formulerades som uppdraget att finna ett behov för ökad effektivitet inom svensk sjukvård, som kan lösas genom implementering av ett realistiskt kliniskt beslutsstöd. Design och metodologi: Uppsatsen är en casestudie där kvalitativ data, samlad genom en litteraturstudie samt intervjuer, användes för att besvara forskningsfrågan. Metodologin som brukades var anpassad efter den unika naturen för forskningen, samt i enighet med syftet av studien. Metoden delades in i fem faser. (1) Finna ett fokusområde, exempelvis en specifik diagnos, där behovet av ett kliniskt beslutsstöd bedömdes högt. (2) Kartlägga vårdkedjan för den identifierade diagnosen. (3) Utveckla hypoteser angående var inom vårdkedjan som  utmaningar skulle kunna lösas med ett kliniskt beslutsstöd. (4) Bekräfta eller förkasta ypoteserna genom intervjuer med relevanta experter. (5) Presentera problemet med det mest trängande behovet efter ett kliniskt beslutsstöd och hur ett sådans skulle utformas. Fynd: Effektivitetsproblemet som kunde lösas bäst via ett kliniskt beslutsstöd identifierades att vara inom området hjärtsviktsbehandling. Det fanns flertalet områden med utvecklingspotential som urskiljdes ur vårdkedjan för hjärtsviktspatienter, och vissa av dessa utmaningar kunde lösas genom utveckling och implementering av specifika kliniska beslutsstöd. Det kliniska beslutsstöd som skulle lösa det mest trängande behovet inom vården idag föreslås vara ett system som hjälper läkare inom vårdcentralerna att identifiera patienter som skulle gagnas av en remiss till en kardiolog. Det föreslagna kliniska beslutsstödet skulle vara både fördelaktigt för vårdpersonal samt patienter samt är realistiskt implementerbart.

Context: Computerized clinical decision support systems (CCDSSs) give practitioners patient-specific care advice and are considered an important increment to electronic clinical documentation and order entry systems. Despite decades of research on CCDSS, results from rigorous clinical evaluations remain mixed and systems vary greatly in design and implementation. Objective: To identify factors differentiating CCDSSs that improve the process of care or patient outcomes from those that do not. Data Sources: We searched major bibliographic databases and scanned reference lists for eligible articles up to January 2010. Study selection: 162 eligible comparisons from randomized controlled trials of CCDSS to non-CCDSS care. We deemed successful those systems that improved either 50% of reported process of care outcomes or 50% of patient outcomes. We extracted system characteristics hypothesized to impact patient care and tested them for association with system effectiveness in logistic models. Results: Our primary analysis showed that CCDSSs presented in electronic health records or order entry systems were less likely to be effective than their counterparts (OR, 0.37; 95% CI, 0.17 to 0.80). Systems more likely to succeed than their counterparts provided advice for patients in addition to practitioners (OR, 2.77; 95% CI, 1.07 to 7.17), required from practitioners a reason to override advice (OR, 11.23; 95% CI, 1.98 to 63.72), or were evaluated by their developers (OR, 4.35; 95% CI, 1.66 to 11.44). These findings remained consistent across different statistical methods, sensitivity analyses, and adjustment for other potentially important factors. Conclusions: We identified several factors that may partially explain why some systems succeed and others fail. Primary studies should investigate the impact and optimal implementation of advice provided to patients and practitioners and advice that requires reasons to be overridden. Researchers should also address the reasons for failure of advice presented within charting and order entry systems. / Master of Science (MSc)

Sistemas de suporte a decisão são utilizados em cenários com incertezas. Uma decisão normalmente é auxiliada por resultados obtidos com ações passadas em problemas semelhantes. Quando um sistema de suporte a decisão incorpora conhecimento específico de uma área, estes recebem o nome de sistemas especialistas. Tal conhecimento especifico é utilizado para inferência juntamente com as informações de entrada a respeito do problema. O objetivo deste trabalho é a avaliação e modelagem de sistemas de auxílio a decisão, foram analisadas duas abordagens para um mesmo problema alvo, sendo uma de gerenciamento do problema e outra de detecção do problema. A abordagem de gerenciamento utiliza redes Bayesianas para modelagem, tanto do conhecimento específico quanto para a inferência. As variáveis utilizadas, as relações de dependência e as probabilidades condicionais entre as variáveis foram extraídas da literatura. A abordagem de detecção do problema utilizou imagens para extração de características seguida de um algoritmo de agrupamento para comparação com a classificação de um especialista. Uma das áreas de aplicação de sistemas especialistas é na área clínica, podendo auxiliar tanto na detecção, diagnóstico e tratamento de doenças. A cárie dental é um problema generalizado que afeta a maioria das pessoas, tanto em países ricos, como em países pobres. Existem poucos sistemas para auxílio no processo de diagnóstico da cárie, sendo a maior parte dos sistemas existentes determinísticos, focando apenas na detecção da lesão. O sistema de gerenciamento da cárie desenvolvido foi apresentado a dois profissionais da odontologia, a opinião deles mostra que está abordagem é promissora e aplicável em campos como a educação e a atenção básica a saúde. Além da apresentação aos profissionais, foram utilizados casos bem estabelecidos da literatura para analisar as sugestões fornecidas pela Rede, e o resultado foi coerente com o cenário real de tomada de decisão. A metodologia de detecção da cárie resultou em um alto valor de acurácia, 96.88%, mostrando que tal metodologia é promissora em comparação com outros trabalhos da área. Além da contribuição para a área de informática odontológica, os resultados mostram que a extração da estrutura e das probabilidades condicionais da rede a partir da literatura é uma metodologia que pode ser utilizada em outras áreas com cenário similar ao do diagnóstico da cárie. Nos próximos passos do projeto alguns pontos referentes a modelagem de sistemas e redes Bayesianas serão analisados, como escalabilidade e testes de validação, tanto quantitativamente como qualitativamente, isto inclui o desenvolvimento de métodos computacionalmente efetivos para a geração de casos aleatórios utilizando o Método de Monte Carlo / Decision support systems are used in uncertainty scenarios; normally a decision is choose using similar problems actions results. Decision support systems could incorporate specific knowledge; such systems are called expert systems. The specific knowledge is used for inference about the problem scenario. This work objective is the evaluation and modeling of decision support systems, we analyzed two distinct approaches for the same problem, one for detection, another for management. The management approach uses Bayesian networks for modeling the specific knowledge and the inference engine. The variables choice, the dependences relationship and the conditional probabilities were extracted from the scientific literature. The detection approach used images and feature extraction to perform a clustering and compare the output labels with a specialist classification. One application of expert systems is clinical, supporting diseases detection, diagnosis and treatment. Dental caries is a generalized problem that affects major part of the population, few systems exists for support the caries diagnostic process, the major part is deterministic, focusing only the detection problem. The caries management system developed here was shown to two odontology professionals, and they opinion encourage such approach to be applied in fields like odontology education and basic health. Beyond this, we used well-established cases to analyze the network output suggestions, the result obtained was coherent with the real decision making scenario. The caries detection approach resulted in a high accuracy, 96.88%, showing that methodology is promising. Besides the contribution for dental informatics field, the results obtained here shows that the extraction of the network structure from the literature could be used in problems similar with caries diagnoses. The project next steps are to analyze some points of systems modeling and Bayesian networks, like scalability and validation tests, both quantitative and qualitative, and including the development of computational effectives methods for the use of Monte Carlo methodology

A Tomografia de Impedância Elétrica (TIE) é uma técnica de imageamento, ainda em desenvolvimento, por meio da qual são extraídas imagens correspondentes à distribuição da impedância elétrica de uma seção transversal de um objeto sob análise a partir de medidas elétricas realizadas em sua superfície. Apesar de seus benefícios e vantagens sobre outras técnicas de imageamento, suas imagens não oferecem uma boa resolução espacial. Em imagens TIE de tórax, um dos maiores desafios reside no tratamento da perfusão pulmonar, pois as perspectivas de uso clínico são inúmeras. Assim sendo, melhorar a localização de seus principais órgãos é um dos grandes objetivos. Com o intuito de melhorar a resolução anatômica foi desenvolvida uma metodologia para identificação de região cardíaca em imagens de tomografia de impedância elétrica de perfusão pulmonar por meio da transformada wavelet, utilizando imagens TIE de porcos. Inicialmente foi realizada uma série de estudos de diferentes abordagens com vistas a identificar aquelas características que pudessem indicar similaridades ou diferenças intrínsecas entre os pixels de diferentes regiões anatômicas. Com base nestes estudos, cinco métodos baseados na análise wavelet foram desenvolvidos. Um primeiro conjunto de experimentos, realizado em um único porco, foi utilizado no desenvolvimento e aperfeiçoamento dos métodos. Posteriormente, outros experimentos, envolvendo quatro porcos em diferentes condições fisiológicas, foram utilizados na avaliação de desempenho destes métodos. As imagens de perfusão wavelet foram comparadas com as imagens de perfusão obtidas pelo método de injeção de uma solução hipertônica, considerada como padrão de referência das imagens de perfusão. A metodologia wavelet proposta por este trabalho foi o método, dentre os cinco desenvolvidos, que obteve os melhores resultados. Ela foi capaz de identificar a região cardíaca de cinco porcos submetidos a diversas condições fisiológicas, demonstrando robustez e resultados muito satisfatórios, não apenas em termos quantitativos, com uma área média da curva ROC de 0,86, mas também na qualidade das imagens obtidas, onde os contornos delimitando a região cardíaca ficaram bem definidos e de formato circular, de acordo com o que se esperava. Portanto, o objetivo maior deste trabalho que era melhorar a resolução espacial de imagens TIE de perfusão pulmonar, foi atingido com excelentes resultados e vantagens adicionais, como por exemplo, a possibilidade de sua implementação em equipamentos TIE de monitoramento do tórax e desta forma colaborar no aperfeiçoamento de sistemas de apoio à decisão médica em ambientes críticos, como é o caso das Unidades de Terapia Intensiva (UTIs). / Electrical Impedance Tomography (EIT) is an imaging technique, still in development, which allows imaging of the distribution of conductivity in a cross section of an object under analysis from electrical measures made on its surface. Despite its benefits and advantages over other imaging techniques, its images still do not offer a good spatial resolution. One of the biggest challenges in EIT thorax images is the treatment of the lung perfusion because the perspectives for clinical use are numerous. Thus, there is a great interest in improving the localization of its main organs. In order to improve the anatomical resolution was developed a methodology for identification of cardiac region in images of electrical impedance tomography of pulmonary perfusion by means of wavelet transform, using EIT images of pigs. Some preliminary studies of different approaches were performed in order to identify those characteristics that would indicate intrinsic similarities or differences among the pixels of different anatomical regions. These studies propitiated the development of five methods based on wavelet transform. A first set of experiments, performed in a single pig, was used in developing and improving of the methods. Subsequently, other experiments, involving four pigs in different physiological conditions, were performed to evaluate the performance of these methods. The wavelet perfusional images were compared with the perfusional images obtained by the method of injection of a hypertonic solution, considered as the perfusional reference standard images. Amongst the five developed methods, the best of them was selected as the wavelet methodology proposed by this work. It was capable to identify the heart region of five pigs under different physiological conditions, demonstrating to robustness and very satisfactory results, not only in quantitative terms, with an average area of the ROC curve of 0.86, but also in the quality of the images, where the contours delimiting the cardiac region were well defined and of circular format, according to what was expected. Therefore, the main objective of this work, that was to improve the spatial resolution of EIT images of pulmonary perfusion, was reached with excellent results and additional benefits such as the possibility of its implementation in EIT equipments for monitoring thorax and thus collaborate in improving of medical decision support systems in critical environments, as for example the Intensive Care Units (ICUs).

Sistemas de suporte a decisão são utilizados em cenários com incertezas. Uma decisão normalmente é auxiliada por resultados obtidos com ações passadas em problemas semelhantes. Quando um sistema de suporte a decisão incorpora conhecimento específico de uma área, estes recebem o nome de sistemas especialistas. Tal conhecimento especifico é utilizado para inferência juntamente com as informações de entrada a respeito do problema. O objetivo deste trabalho é a avaliação e modelagem de sistemas de auxílio a decisão, foram analisadas duas abordagens para um mesmo problema alvo, sendo uma de gerenciamento do problema e outra de detecção do problema. A abordagem de gerenciamento utiliza redes Bayesianas para modelagem, tanto do conhecimento específico quanto para a inferência. As variáveis utilizadas, as relações de dependência e as probabilidades condicionais entre as variáveis foram extraídas da literatura. A abordagem de detecção do problema utilizou imagens para extração de características seguida de um algoritmo de agrupamento para comparação com a classificação de um especialista. Uma das áreas de aplicação de sistemas especialistas é na área clínica, podendo auxiliar tanto na detecção, diagnóstico e tratamento de doenças. A cárie dental é um problema generalizado que afeta a maioria das pessoas, tanto em países ricos, como em países pobres. Existem poucos sistemas para auxílio no processo de diagnóstico da cárie, sendo a maior parte dos sistemas existentes determinísticos, focando apenas na detecção da lesão. O sistema de gerenciamento da cárie desenvolvido foi apresentado a dois profissionais da odontologia, a opinião deles mostra que está abordagem é promissora e aplicável em campos como a educação e a atenção básica a saúde. Além da apresentação aos profissionais, foram utilizados casos bem estabelecidos da literatura para analisar as sugestões fornecidas pela Rede, e o resultado foi coerente com o cenário real de tomada de decisão. A metodologia de detecção da cárie resultou em um alto valor de acurácia, 96.88%, mostrando que tal metodologia é promissora em comparação com outros trabalhos da área. Além da contribuição para a área de informática odontológica, os resultados mostram que a extração da estrutura e das probabilidades condicionais da rede a partir da literatura é uma metodologia que pode ser utilizada em outras áreas com cenário similar ao do diagnóstico da cárie. Nos próximos passos do projeto alguns pontos referentes a modelagem de sistemas e redes Bayesianas serão analisados, como escalabilidade e testes de validação, tanto quantitativamente como qualitativamente, isto inclui o desenvolvimento de métodos computacionalmente efetivos para a geração de casos aleatórios utilizando o Método de Monte Carlo / Decision support systems are used in uncertainty scenarios; normally a decision is choose using similar problems actions results. Decision support systems could incorporate specific knowledge; such systems are called expert systems. The specific knowledge is used for inference about the problem scenario. This work objective is the evaluation and modeling of decision support systems, we analyzed two distinct approaches for the same problem, one for detection, another for management. The management approach uses Bayesian networks for modeling the specific knowledge and the inference engine. The variables choice, the dependences relationship and the conditional probabilities were extracted from the scientific literature. The detection approach used images and feature extraction to perform a clustering and compare the output labels with a specialist classification. One application of expert systems is clinical, supporting diseases detection, diagnosis and treatment. Dental caries is a generalized problem that affects major part of the population, few systems exists for support the caries diagnostic process, the major part is deterministic, focusing only the detection problem. The caries management system developed here was shown to two odontology professionals, and they opinion encourage such approach to be applied in fields like odontology education and basic health. Beyond this, we used well-established cases to analyze the network output suggestions, the result obtained was coherent with the real decision making scenario. The caries detection approach resulted in a high accuracy, 96.88%, showing that methodology is promising. Besides the contribution for dental informatics field, the results obtained here shows that the extraction of the network structure from the literature could be used in problems similar with caries diagnoses. The project next steps are to analyze some points of systems modeling and Bayesian networks, like scalability and validation tests, both quantitative and qualitative, and including the development of computational effectives methods for the use of Monte Carlo methodology