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Visar resultat 1 - 5 av 355 avhandlingar som matchar ovanstående sökkriterier.

  1. 1. Algorithmically Guided Information Visualization : Explorative Approaches for High Dimensional, Mixed and Categorical Data

    Författare :Sara Johansson Fernstad; Mikael Jern; Jimmy Johansson; Jane Shaw; Matthew O. Ward; Linköpings universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Information visualization; data mining; high dimensional data; categorical data; mixed data;

    Sammanfattning : Facilitated by the technological advances of the last decades, increasing amounts of complex data are being collected within fields such as biology, chemistry and social sciences. The major challenge today is not to gather data, but to extract useful information and gain insights from it. LÄS MER

  3. 2. Sentiment and Stance Visualization of Textual Data for Social Media

    Författare :Kostiantyn Kucher; Andreas Kerren; Carita Paradis; Magnus Sahlgren; Ross Maciejewski; Linnéuniversitetet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; stance visualization; sentiment visualization; text visualization; stance analysis; sentiment analysis; opinion mining; visualization; interaction; visual analytics; NLP; text mining; text analytics; social media; Informations- och programvisualisering; Information and software visualization;

    Sammanfattning : Rapid progress in digital technologies has transformed the world in many ways during the past few decades, in particular, with the new means of communication such as social media. Social media platforms typically rely on textual data produced or shared by the users in multiple timestamped posts. LÄS MER

  4. 3. Image Based Visualization Methods for Meteorological Data

    Författare :Björn Olsson; Anders Ynnerman; Reiner Lenz; Anders Hast; Linköpings universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Visualization; Meteorological Data; Artificial Neural Networks; High-Dynamic-Range images; Satellite Data; Classification; Computer science; Datavetenskap;

    Sammanfattning : Visualization is the process of constructing methods, which are able to synthesize interesting and informative images from data sets, to simplify the process of interpreting the data. In this thesis a new approach to construct meteorological visualization methods using neural network technology is described. LÄS MER

  5. 4. Advancing Clinical Decision Support Using Machine Learning & the Internet of Medical Things : Enhancing COVID-19 & Early Sepsis Detection

    Författare :Mahbub Ul Alam; Rahim Rahmani; Jaakko Hollmén; Sadok Ben Yahia; Stockholms universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Internet of Medical Things; Patient-Centric Healthcare; Clinical Decision Support System; Predictive Modeling in Healthcare; Health Informatics; Healthcare analytics; COVID-19; Sepsis; COVID-19 Detection; Early Sepsis Detection; Lung Segmentation Detection; Medical Data Annotation Scarcity; Medical Data Sparsity; Medical Data Heterogeneity; Medical Data Security Privacy; Practical Usability Enhancement; Low-End Device Adaptability; Medical Significance; Interpretability; Visualization; LIME; SHAP; Grad-CAM; LRP; Electronic Health Records; Thermal Image; Tabular Medical Data; Chest X-ray; Machine Learning; Deep Learning; Federated Learning; Semi-Supervised Machine Learning; Multi-Task Learning; Transfer Learning; Multi-Modality; Natural Language Processing; ClinicalBERT; GAN; data- och systemvetenskap; Computer and Systems Sciences;

    Sammanfattning : This thesis presents a critical examination of the positive impact of Machine Learning (ML) and the Internet of Medical Things (IoMT) for advancing the Clinical Decision Support System (CDSS) in the context of COVID-19 and early sepsis detection.It emphasizes the transition towards patient-centric healthcare systems, which necessitate personalized and participatory care—a transition that could be facilitated by these emerging fields. LÄS MER

  7. 5. Web Applications for Large-Scale Decision Support : Preference Elicitation, Modeling and Visualization

    Författare :Samuel Bohman; Aron Larsson; Bo Sundgren; Majlender Peter; Göran Cars; Øystein Sæbø; Stockholms universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; World Wide Web; Decision Support Systems; Data Visualization; Man-Machine-Interaction MMI ; människa-maskin-interaktion MMI ;

    Sammanfattning : This thesis addresses the lack of effective and efficient technology design in current e-participation research by investigating two approaches that yet have not been explored to any great extent in the literature: decision science and data visualization. It is concerned with the problem of how to combine techniques from these two fields to achieve decision support in the context of e-participation; from preference elicitation and modeling to data analysis, visualization and final recommendations, such that it can provide value to practitioners. LÄS MER