Estratégia de recuperação e análise de informações epidemiológicas com visualização georreferenciada sobre dados médicos heterogêneos

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Ciência da Computação, Florianópolis, 2016.A análise sobre dados gerados por sistemas médicos tem permitido aos epidemiologistas e profissionais da saúde o monitoramento e análise epidemiológica de doenças. Como ferramenta de suporte para aquisição de dados sobre doenças, a telemedicina oferece a capacidade de coletar e organizar os dados de pacientes, auxiliando a vigilância epidemiológica por meio da identificação e acompanhamento de questões de saúde pública. Este trabalho propõe uma arquitetura, chamada GISTelemed, para recuperação, análise e visualização epidemiológica georreferenciada integrada ao Sistema Integrado Catarinense de Telemedicina e Telessaúde -- STT/SC. A abordagem apresentada permite a indexação de dados estruturados (banco de dados relacional) e semiestruturados (DICOM Structured Report) e a visualização dos resultados em tabelas, gráficos estatísticos e mapas interativos. Resultados obtidos por meio de um estudo de caso indicam uma percepção positiva em relação à utilidade, satisfação, eficácia e eficiência do GISTelemed por médicos especialistas, epidemiologistas e gestores de saúde.Abstract : Analysis about data generated by medical systems have allowed health professionals and epidemiologists to monitor possible outbreaks. As a support tool for the acquisition of data on diseases, telemedicine offers the ability to collect and organize data of patients, assisting epidemiological surveillance through the identification and monitoring of public health issues. This paper presents GISTelemed, an georeferenced epidemiological analysis architecture developed as part of the Santa Catarina State Integrated Telemedicine and Telehealth System --STT/SC, a statewide telemedicine infrastructure in Brazil. The approach presented allows indexing of structured (relational) and semi-structured (DICOM Structured Report) data, search and retrieval based on free-text and structured query and display georeferenced information on tables and interactive maps, as a module integrated into a telemedicine application. Results obtained through a case study indicate a positive perception of the utility, satisfaction, effectiveness and efficiency of GISTelemed by medical specialists, epidemiologists and health administrators

Modeling Complex High Level Interactions in the Process of Visual Mining

Visual Mining refers to the human analytical process that uses visual representations of raw data and makes suitable inferences. During this analytical process, users are engaged in complex cognitive activities such as decision making, problem solving, analytical reasoning and learning. Now a days, users typically use interactive visualization tools, which we call as visual mining support tools (VMSTs), to mediate their interactions with the information present in visual representations of raw data and also to support their complex cognitive activities when performing visual mining. VMSTs have two main components: visual representation and interaction. Even though, these two components are fundamental aspects of VMSTs, the research on visual representation has received the most attention. It is still unclear how to design interactions which can properly support users in performing complex cognitive activities during the visual mining process. Although some fundamental concepts and techniques regarding interaction design have been in place for a while, many established researchers are of the opinion that we do not yet have a generalized, principled, and systematic understanding of interaction components of these VMSTs, and how interactions should be analyzed, designed, and integrated to support complex cognitive activities. Many researchers have recommended that one way to address this problem is through appropriate characterization of interactions in the visual mining process. Models that provide classifications of interactions have indeed been proposed in the visualization research community. While these models are important contributions for the visualization research community, they often characterize interactions at lower levels of human information interaction and high level interactions are not well addressed. In addition, some of these models are not designed to model user activity; rather they are most applicable for representing a system’s response to user activity and not the user activity itself. In this thesis, we address this problem through characterization of the interaction space of visual mining at the appropriate level. Our main contribution in this research is the discovery of a small set of classification criteria which can comprehensively characterize the interaction space of visual mining involving interactions with VMSTs for performing complex cognitive activities. These complex cognitive activities are modeled through visual mining episodes, a coherent set of activities consisting of visual mining strategies (VMSs). Using the classification criteria, VMSs are simply described as combinations of different values of these criteria. By considering all combinations, we can comprehensively cover the interaction space of visual mining. Our VMS interaction space model is unique in identifying the activity tier, a granularity of interactions (high level) which supports performance of complex cognitive activities through interactions with visual information using VMSTs. As further demonstration of the utility of this VMS interaction space model, we describe the formulation of an inspection framework which can provide quantitative measures for the support provided by VMSTs for complex cognitive activities in visual mining. This inspection framework, which has enabled us to produce a new simpler evaluation method for VMSTs in comparison to existing evaluation methods, is based soundly on existing theories and models. Both the VMS interaction space model and the inspection framework present many interesting avenues for further research

Steps in transforming the Missouri Cancer Registry (MCR) from anincidence registry to a survival registry : estimate and interactively visualize female breast cancer burden in Missouri senatorial districts and assess the usability of the Missouri Cancer Registry and Research Center's (MCRARC'S) published interactive maps

Female breast cancer (FBC) is the most common invasive cancer among women of all races and ethnicities in the United States (US). About 12 percent of women in the United States will be diagnosed with breast cancer at some point in their lives. The Missouri Cancer Registry (MCR) needs to be transformed from an incidence registry to a survival registry to accurately measure the impact of Missouri public health programs. In addition, it needs to use interactive mapping reports of maps and statistics to improve data visualization. Many studies have concluded the importance of estimation of cancer incidence, mortality and survival together. We aimed to estimate breast cancer burden in Missouri during recent years in terms of breast cancer incidence, mortality and survival rates; to visualize these results; and to assess the usability of the Missouri Cancer Registry and Research Center's (MCR-ARC's) interactive maps and profile reports. FBC survival data were calculated from 2004 to 2010 after matching MCR's FBC cases with Missouri's state death records, the Social Security Death Index (SSDI) and the National Death Index (NDI). FBC incidence and mortality rates were measured from 2008 to 2012. Survival and incidence data were measured for each senate district by age, race, stage and grade at diagnosis. Mortality data was measured for each county and Senate District Groups of Counties by age and race. The rates were visualized using Instant Atlas. A scoping review and a two round usability testing study were conducted to explore perceptions of public health professionals about the use of geographic information systems and to assess the usability of the MCR-ARC's published maps. The dissertation results could be very informative for Missouri decision makers and public health leaders. Instant Atlas reports might enhance the communication between collaborators from different fields related to breast cancer and to disseminate female breast cancer data and inform health professionals and the public.Includes biblographical reference

Evaluating human-centered approaches for geovisualization

Working with two small group of domain experts I evaluate human-centered approaches to application development which are applicable to geovisualization, following an ISO13407 taxonomy that covers context of use, eliciting requirements, and design. These approaches include field studies and contextual analysis of subjects' context; establishing requirements using a template, via a lecture to communicate geovisualization to subjects and by communicating subjects' context to geovisualization experts with a scenario; autoethnography to understand the geovisualization design process; wireframe, paper and digital interactive prototyping with alternative protocols; and a decision making process for prioritising application improvement. I find that the acquisition and use of real user data is key; that a template approach and teaching subjects about visualization tools and interactions both fail to elicit useful requirements for a visualization application. Consulting geovisualization experts with a scenario of user context and samples of user data does yield suggestions for tools and interactions of use to a visualization designer. The complex and composite natures of both visualization and human-centered domains, incorporating learning from both domains, with user context, makes design challenging. Wireframe, paper and digital interactive prototypes mediate between the user and visualization domains successfully, eliciting exploratory behaviour and suggestions to improve prototypes. Paper prototypes are particularly successful at eliciting suggestions and especially novel visualization improvements. Decision-making techniques prove useful for prioritising different possible improvements, although domain subjects select data-related features over more novel alternative and rank these more inconsistently. The research concludes that understanding subject context of use and data is important and occurs throughout the process of engagement with domain experts, and that standard requirements elicitation techniques are unsuccessful for geovisualization. Engagement with subjects at an early stage with simple prototypes incorporating real subject data and moving to successively more complex prototypes holds the best promise for creating successful geovisualization applications