Search for dissertations about: "machine learning on medical health data"

Showing result 1 - 5 of 54 swedish dissertations containing the words machine learning on medical health data.

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

    Author : Mahbub Ul Alam; Rahim Rahmani; Jaakko Hollmén; Sadok Ben Yahia; Stockholms universitet; []
    Keywords : 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;

    Abstract : 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. READ MORE

  4. 2. Learning from Complex Medical Data Sources

    Author : Jonathan Rebane; Panagiotis Papapetrou; Isak Samsten; Myra Spiliopoulou; Stockholms universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Machine Learning; Data Science; Healthcare; Complex Data; Explainable AI; Deep Learning; data- och systemvetenskap; Computer and Systems Sciences;

    Abstract : Large, varied, and time-evolving data sources can be observed across many domains and present a unique challenge for classification problems, in which traditional machine learning approaches must be adapted to accommodate for the complex nature of such data. Across most domains, there is also a need for machine learning models that are both well-performing and interpretable, to help provide explanations of a model's decisions that stakeholders can trust and take appropriate actions with. READ MORE

  5. 3. Data-driven personalized healthcare : Towards personalized interventions via reinforcement learning for Mobile Health

    Author : Alexander Galozy; Sławomir Nowaczyk; Mattias Ohlsson; Fredrik Johansson; Högskolan i Halmstad; []
    Keywords : MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Information Driven Care; Electronic Health Records; Machine Learning; Reinforcement Learning;

    Abstract : Medical and technological advancement in the last century has led to the unprecedented increase of the populace's quality of life and lifespan. As a result, an ever-increasing number of people live with chronic health conditions that require long-term treatment, resulting in increased healthcare costs and managerial burden to the healthcare provider. READ MORE

  6. 4. Machine learning applications in healthcare

    Author : Ana Luiza Dallora Moraes; Peter Anderberg; Johan Sanmartin Berglund; Martin Boldt; Arianit Kurti; Blekinge Tekniska Högskola; []
    Keywords : MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Machine learning; Healthcare; Diagnosis; Prognosis; Age assessment; Bone age assessment; Dementia; Applied health technology; Tillämpad hälsoteknik; Applied Health Technology;

    Abstract : Healthcare is an important and high cost sector that involves many decision-making tasks based on the analysis of data, from its primary activities up till management itself. A technology that can be useful in an environment as data-intensive as healthcare is machine learning. READ MORE

  7. 5. eVisits in the digital era of Swedish primary care

    Author : Artin Entezarjou; Allmänmedicin och samhällsmedicin; []
    Keywords : MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Telemedicine; Telehealth; Primary care; Antibiotic prescribing; Health care utilization; eHealth; eVisits; Family medicine; Machine learning; Artificial intelligence; Qualitative approaches; Implementation science; Change management; Staff attitudes; Triage; Digital health; Digital visits; Automation systems; Decision support in healthcare; Health care systems; Digi-physical care; Team work;

    Abstract : Objective: To evaluate asynchronous digital visits (eVisits) with regard to digital communication, clinical decisionmaking,and subsequent care utilization in the digital era of primary care in Sweden.Methods: A mixed-methods approach was adopted across the various papers in the thesis, with all studiesevaluating the eVisit platform Flow in various clinical contexts. READ MORE