Sökning: "Decision support in healthcare"

Visar resultat 1 - 5 av 102 avhandlingar innehållade orden Decision support in healthcare.

1. 1. Pathways for older patients in acute situations and involved actors' experiences of decision-making in ambulatory care

   Författare :Elin-Sofie Forsgärde; Carina Elmqvist; Bengt Fridlund; Mattias Rööst; Anders Svensson; Elisabeth Lindberg; Linnéuniversitetet; []
   Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Acute situation; aged; ambulatory care; decision making; pathways; support; Vårdvetenskap; Caring Science;

   Sammanfattning : Aim: The overall aim was to describe and compare pathways for older patients and the involved actors’ experiences of decision-making in acute situations in ambulatory care.Methods: The overall three-fold design, comprising exploratory, descriptive as well as comparative ones, was conducted inductively, including a mixed method with a convergent integrated approach to empirical data. LÄS MER

3. 2. 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

4. 3. On Decision Support in Participatory Medicine Supporting Health Care Empowerment

   Författare :Kerstin Ådahl; Blekinge Tekniska Högskola; []
   Nyckelord :SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Decision support; CDSS; EHR; Patient safety; Patient empowerment; Participatory medicine; Patient-centered collaborative practice;

   Sammanfattning : The task of ensuring Patient Safety is, more than ever, central in Healthcare. The report “To Err is Human” [Kohn et al. 2000], was revealing alarming numbers of incidents, injuries and deaths caused by deficiencies in healthcare activities. The book initiated assessment and change of Healthcare methods and procedures. LÄS MER

5. 4. Logistics Management in a Healthcare Context : Methodological development for describing and evaluating a healthcare organisation as a logistics system

   Författare :Malin Wiger; Håkan Aronsson; Mattias Elg; Linköpings universitet; []
   Nyckelord :;

   Sammanfattning : This thesis tests whether logistics knowledge, theories and principles can be used to provide potential patient flow efficiency improvements. By emphasizing an ideal logistics system by means of its main features and then using these to evaluate two different healthcare organisations, it is assumed that knowledge regarding patient flows can be obtained and potentials for improvement highlighted. LÄS MER

7. 5. Voice for Decision Support in Healthcare Applied to Chronic Obstructive Pulmonary Disease Classification : A Machine Learning Approach

   Författare :Alper Idrisoglu; Johan Sanmartin Berglund; Blekinge Tekniska Högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Automated decision-support; Classification; Machine Learning; Voice-affecting disorders; Voice dataset; Voice Features; Chronic Obstructive pulmonary disease COPD ; Tillämpad hälsoteknik; Applied Health Technology;

   Sammanfattning : Background: Advancements in machine learning (ML) techniques and voice technology offer the potential to harness voice as a new tool for developing decision-support tools in healthcare for the benefit of both healthcare providers and patients. Motivated by technological breakthroughs and the increasing integration of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare, numerous studies aim to investigate the diagnostic potential of ML algorithms in the context of voice-affecting disorders. LÄS MER