61 research outputs found

    Sistemas interativos e distribuídos para telemedicina

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    doutoramento Ciências da ComputaçãoDurante as últimas décadas, as organizações de saúde têm vindo a adotar continuadamente as tecnologias de informação para melhorar o funcionamento dos seus serviços. Recentemente, em parte devido à crise financeira, algumas reformas no sector de saúde incentivaram o aparecimento de novas soluções de telemedicina para otimizar a utilização de recursos humanos e de equipamentos. Algumas tecnologias como a computação em nuvem, a computação móvel e os sistemas Web, têm sido importantes para o sucesso destas novas aplicações de telemedicina. As funcionalidades emergentes de computação distribuída facilitam a ligação de comunidades médicas, promovem serviços de telemedicina e a colaboração em tempo real. Também são evidentes algumas vantagens que os dispositivos móveis podem introduzir, tais como facilitar o trabalho remoto a qualquer hora e em qualquer lugar. Por outro lado, muitas funcionalidades que se tornaram comuns nas redes sociais, tais como a partilha de dados, a troca de mensagens, os fóruns de discussão e a videoconferência, têm o potencial para promover a colaboração no sector da saúde. Esta tese teve como objetivo principal investigar soluções computacionais mais ágeis que permitam promover a partilha de dados clínicos e facilitar a criação de fluxos de trabalho colaborativos em radiologia. Através da exploração das atuais tecnologias Web e de computação móvel, concebemos uma solução ubíqua para a visualização de imagens médicas e desenvolvemos um sistema colaborativo para a área de radiologia, baseado na tecnologia da computação em nuvem. Neste percurso, foram investigadas metodologias de mineração de texto, de representação semântica e de recuperação de informação baseada no conteúdo da imagem. Para garantir a privacidade dos pacientes e agilizar o processo de partilha de dados em ambientes colaborativos, propomos ainda uma metodologia que usa aprendizagem automática para anonimizar as imagens médicasDuring the last decades, healthcare organizations have been increasingly relying on information technologies to improve their services. At the same time, the optimization of resources, both professionals and equipment, have promoted the emergence of telemedicine solutions. Some technologies including cloud computing, mobile computing, web systems and distributed computing can be used to facilitate the creation of medical communities, and the promotion of telemedicine services and real-time collaboration. On the other hand, many features that have become commonplace in social networks, such as data sharing, message exchange, discussion forums, and a videoconference, have also the potential to foster collaboration in the health sector. The main objective of this research work was to investigate computational solutions that allow us to promote the sharing of clinical data and to facilitate the creation of collaborative workflows in radiology. By exploring computing and mobile computing technologies, we have designed a solution for medical imaging visualization, and developed a collaborative system for radiology, based on cloud computing technology. To extract more information from data, we investigated several methodologies such as text mining, semantic representation, content-based information retrieval. Finally, to ensure patient privacy and to streamline the data sharing in collaborative environments, we propose a machine learning methodology to anonymize medical images

    The Artificial Intelligence in Digital Pathology and Digital Radiology: Where Are We?

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    This book is a reprint of the Special Issue entitled "The Artificial Intelligence in Digital Pathology and Digital Radiology: Where Are We?". Artificial intelligence is extending into the world of both digital radiology and digital pathology, and involves many scholars in the areas of biomedicine, technology, and bioethics. There is a particular need for scholars to focus on both the innovations in this field and the problems hampering integration into a robust and effective process in stable health care models in the health domain. Many professionals involved in these fields of digital health were encouraged to contribute with their experiences. This book contains contributions from various experts across different fields. Aspects of the integration in the health domain have been faced. Particular space was dedicated to overviewing the challenges, opportunities, and problems in both radiology and pathology. Clinal deepens are available in cardiology, the hystopathology of breast cancer, and colonoscopy. Dedicated studies were based on surveys which investigated students and insiders, opinions, attitudes, and self-perception on the integration of artificial intelligence in this field

    MATURITY MODEL FOR HEALTHCARE CLOUD SECURITY

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    Management of security across eHealth cloud services is a major organizational challenge that healthcare organizations seek to resolve in order to aid their trusts in cloud and increase the adoption of cloud services in healthcare. The organizational challenges regarding implementations of technical security solutions are the major limiting factors for the adoption of the eHealth cloud. As such, the aim of this research will focus on developing a security maturity model, which will help healthcare organizations to provide a description of the application of their cloud security services, and an assessment and improvement of their cloud security services over time, as well as to guide and educate relevant stakeholders concerning the optimization of their security practices. The identified gaps in the review are in the aspect of adoption – the maturity models are either too complicated to implement, or they require the healthcare organization’s processes to be refined to suit the maturity model’s implementation. The Maturity Model for Healthcare Cloud Security (M2HCS) was developed using the Design Science Research Methodology (DSRM). It was validated using a formulated case study, web-based survey and interviews with practitioners, DSRM framework, and feedback from scientific community. The novel contribution of this research is the proposal of the model. M2HCS is a high level, holistic model that can be used to support and promote healthcare organization’s usable security practices against cyber and cloud security attacks

    An Autoethnographic Account of Innovation at the US Department of Veterans Affairs

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    The history of the U.S. Department of Veterans Affairs (VA) health information technology (HIT) has been characterized by both enormous successes and catastrophic failures. While the VA was once hailed as the way to the future of twenty-first-century health care, many programs have been mismanaged, delayed, or flawed, resulting in the waste of hundreds of millions of taxpayer dollars. Since 2015 the U.S. Government Accountability Office (GAO) has designated HIT at the VA as being susceptible to waste, fraud, and mismanagement. The timely central research question I ask in this study is, can healthcare IT at the VA be healed? To address this question, I investigate a HIT case study at the VA Center of Innovation (VACI), originally designed to be the flagship initiative of the open government transformation at the VA. The Open Source Electronic Health Record Alliance (OSEHRA) was designed to promote the open innovation ecosystem public-private-academic partnership. Based on my fifteen years of experience at the VA, I use an autoethnographic methodology to make a significant value-added contribution to understanding and modeling the VA’s approach to innovation. I use several theoretical information system framework models including People, Process, and Technology (PPT), Technology, Organization and Environment (TOE), and Technology Adaptive Model (TAM) and propose a new adaptive theory to understand the inability of VA HIT to innovate. From the perspective of people and culture, I study retaliation against whistleblowers, organization behavioral integrity, and lack of transparency in communications. I examine the VA processes, including the different software development methodologies used, the development and operations process (DevOps) of an open-source application developed at VACI, the Radiology Protocol Tool Recorder (RAPTOR), a Veterans Health Information Systems and Technology Architecture (VistA) radiology workflow module. I find that the VA has chosen to migrate away from inhouse application software and buy commercial software. The impact of these People, Process, and Technology findings are representative of larger systemic failings and are appropriate examples to illustrate systemic issues associated with IT innovation at the VA. This autoethnographic account builds on first-hand project experience and literature-based insights

    Arquiteturas federadas para integração de dados biomédicos

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    Doutoramento Ciências da ComputaçãoThe last decades have been characterized by a continuous adoption of IT solutions in the healthcare sector, which resulted in the proliferation of tremendous amounts of data over heterogeneous systems. Distinct data types are currently generated, manipulated, and stored, in the several institutions where patients are treated. The data sharing and an integrated access to this information will allow extracting relevant knowledge that can lead to better diagnostics and treatments. This thesis proposes new integration models for gathering information and extracting knowledge from multiple and heterogeneous biomedical sources. The scenario complexity led us to split the integration problem according to the data type and to the usage specificity. The first contribution is a cloud-based architecture for exchanging medical imaging services. It offers a simplified registration mechanism for providers and services, promotes remote data access, and facilitates the integration of distributed data sources. Moreover, it is compliant with international standards, ensuring the platform interoperability with current medical imaging devices. The second proposal is a sensor-based architecture for integration of electronic health records. It follows a federated integration model and aims to provide a scalable solution to search and retrieve data from multiple information systems. The last contribution is an open architecture for gathering patient-level data from disperse and heterogeneous databases. All the proposed solutions were deployed and validated in real world use cases.A adoção sucessiva das tecnologias de comunicação e de informação na área da saúde tem permitido um aumento na diversidade e na qualidade dos serviços prestados, mas, ao mesmo tempo, tem gerado uma enorme quantidade de dados, cujo valor científico está ainda por explorar. A partilha e o acesso integrado a esta informação poderá permitir a identificação de novas descobertas que possam conduzir a melhores diagnósticos e a melhores tratamentos clínicos. Esta tese propõe novos modelos de integração e de exploração de dados com vista à extração de conhecimento biomédico a partir de múltiplas fontes de dados. A primeira contribuição é uma arquitetura baseada em nuvem para partilha de serviços de imagem médica. Esta solução oferece um mecanismo de registo simplificado para fornecedores e serviços, permitindo o acesso remoto e facilitando a integração de diferentes fontes de dados. A segunda proposta é uma arquitetura baseada em sensores para integração de registos electrónicos de pacientes. Esta estratégia segue um modelo de integração federado e tem como objetivo fornecer uma solução escalável que permita a pesquisa em múltiplos sistemas de informação. Finalmente, o terceiro contributo é um sistema aberto para disponibilizar dados de pacientes num contexto europeu. Todas as soluções foram implementadas e validadas em cenários reais

    Optimization of the management and triage of stroke patients in the acute phase

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    Acute ischemic stroke (AIS) due to a large vessel occlusion (LVO) is a devastating disease associated with high rates of morbidity and mortality. Currently, the standard of care for patients presenting with a LVO is removal of the clot with specialized catheters (endovascular treatment). Although endovascular treatment has substantially improved the outcomes of AIS patients, still roughly 50% of patients suffer from severe disability or death. Due to the very high time dependency of the treatment effect, strategies to reduce time to treatment to a minimum are highly warranted. As of now no consensus exists on the best possible triage strategy for suspected AIS patients. One possible approach to reduce time delays within the hospital is to transport patients directly from the emergency room to the angiography room for diagnosis of a vessel occlusion and subsequent treatment (One-Stop management) instead of transporting the patient first to the CT room and after diagnosis of a vessel occlusion to the angiography room for treatment (traditional triage pathway). Imaging in the One-Stop management pathway is done with flat detector CT (FDCT) instead of traditional multidetector CT (MDCT). Many clinicians are still hesitant to use this triage pathway due to missing data and lower confidence in the quality of FDCT imaging. Therefore, several research gaps and challenges remain for the optimization of the management and triage of suspected stroke patients in the acute phase, of which we selected three aspects to focus on in the following topics that comprise this PhD thesis. The first topic focusses on the radiation burden caused by alternative imaging modalities in AIS patients. While flat-detector CT (FDCT) imaging becomes more and more acknowledged as an alternative imaging modality for the diagnosis of an AIS and an LVO, the effective dose to patient of FDCT protocols was not evaluated systematically. For the widespread implementation of FDCT as an imaging modality it must be secured that no excess harm is caused due to a higher burden of radiation. We therefore measured the effective dose to patient and the eye lens dose on two angiography systems and compared it with measurements on the latest generation of commonly used MDCT systems. The second topic focusses on the presentation of suspected AIS patients. As there is no high-level evidence for the implementation of a One Stop management approach, we are planning to conduct a randomized controlled trial. However, for the conduct of such a trial it is important to have reliable information of the expected patient cohort. We therefore analyzed all patients presenting to a tertiary university hospital in one year to give an estimate on the patient collectives expected for such a trial. The data can further be used to plan resources accordingly in times of expanding indications for endovascular treatment of AIS patients. The third and final topic summarizes the available evidence regarding One-Stop management and direct to angiography approaches in a systematic review and meta-analysis. It gives an overview over the research conducted so far in this field and is the foundation for the planning of a randomized controlled trial evaluating a One-Stop management approach for suspected AIS patients

    Web-based Stereoscopic Collaboration for Medical Visualization

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    Medizinische Volumenvisualisierung ist ein wertvolles Werkzeug zur Betrachtung von Volumen- daten in der medizinischen Praxis und Lehre. Eine interaktive, stereoskopische und kollaborative Darstellung in Echtzeit ist notwendig, um die Daten vollständig und im Detail verstehen zu können. Solche Visualisierung von hochauflösenden Daten ist jedoch wegen hoher Hardware- Anforderungen fast nur an speziellen Visualisierungssystemen möglich. Remote-Visualisierung wird verwendet, um solche Visualisierung peripher nutzen zu können. Dies benötigt jedoch fast immer komplexe Software-Deployments, wodurch eine universelle ad-hoc Nutzbarkeit erschwert wird. Aus diesem Sachverhalt ergibt sich folgende Hypothese: Ein hoch performantes Remote- Visualisierungssystem, welches für Stereoskopie und einfache Benutzbarkeit spezialisiert ist, kann für interaktive, stereoskopische und kollaborative medizinische Volumenvisualisierung genutzt werden. Die neueste Literatur über Remote-Visualisierung beschreibt Anwendungen, welche nur reine Webbrowser benötigen. Allerdings wird bei diesen kein besonderer Schwerpunkt auf die perfor- mante Nutzbarkeit von jedem Teilnehmer gesetzt, noch die notwendige Funktion bereitgestellt, um mehrere stereoskopische Präsentationssysteme zu bedienen. Durch die Bekanntheit von Web- browsern, deren einfach Nutzbarkeit und weite Verbreitung hat sich folgende spezifische Frage ergeben: Können wir ein System entwickeln, welches alle Aspekte unterstützt, aber nur einen reinen Webbrowser ohne zusätzliche Software als Client benötigt? Ein Proof of Concept wurde durchgeführt um die Hypothese zu verifizieren. Dazu gehörte eine Prototyp-Entwicklung, deren praktische Anwendung, deren Performanzmessung und -vergleich. Der resultierende Prototyp (CoWebViz) ist eines der ersten Webbrowser basierten Systeme, welches flüssige und interaktive Remote-Visualisierung in Realzeit und ohne zusätzliche Soft- ware ermöglicht. Tests und Vergleiche zeigen, dass der Ansatz eine bessere Performanz hat als andere ähnliche getestete Systeme. Die simultane Nutzung verschiedener stereoskopischer Präsen- tationssysteme mit so einem einfachen Remote-Visualisierungssystem ist zur Zeit einzigartig. Die Nutzung für die normalerweise sehr ressourcen-intensive stereoskopische und kollaborative Anatomieausbildung, gemeinsam mit interkontinentalen Teilnehmern, zeigt die Machbarkeit und den vereinfachenden Charakter des Ansatzes. Die Machbarkeit des Ansatzes wurde auch durch die erfolgreiche Nutzung für andere Anwendungsfälle gezeigt, wie z.B. im Grid-computing und in der Chirurgie

    Med-e-Tel 2013

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