Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 27 for “"clinical decision support systems"”.
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An evaluation method for the evaluation of big data based streaming analytic clinical decision support systems
… presents a methodology for evaluating a scalable clinical decision support systems (CDSS) that uses high frequency streaming physiological data using a holistic approach that includes the presence of population health indicators. The plan applies concepts and uses indicators suggested in the …
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Predicting Personalized Pathological Risks and Dynamics in Cardiology - How to Exploit Data-Driven Approaches in Clinical Decision Support Systems
L'abstract è presente nell'allegato / the abstract is in the attachment
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Evaluation of the Effect of the Clinical-Decision-Support Systems on Diabetes Management: A Multivariate Meta-Analysis Comparison with Univariate Meta-Analysis
… goal of this study was to evaluate the effect of clinical decision support systems CDSS on diabetes care management by conducting three separate univariate meta-analyses and one multivariate meta-analysis. CDSS are health information technology systems that analyze data within electronic health …
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Machine Learning-based Feature Selection and Optimisation for Clinical Decision Support Systems. Optimal Data-driven Feature Selection Methods for Binary and Multi-class Classification Problems: Towards a Minimum Viable Solution for Predicting Early Diagnosis and Prognosis
… of prior work by Luca Parisi is submitted in support of a PhD by Published Work. The work focuses on deriving accurate, reliable and explainable clinical decision support systems as minimum clinically viable solutions leveraging Machine Learning (ML) and evolutionary algorithms, for the first …
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Machine Learning-based Feature Selection and Optimisation for Clinical Decision Support Systems. Optimal Data-driven Feature Selection Methods for Binary and Multi-class Classification Problems: Towards a Minimum Viable Solution for Predicting Early Diagnosis and Prognosis
… of prior work by Luca Parisi is submitted in support of a PhD by Published Work. The work focuses on deriving accurate, reliable and explainable clinical decision support systems as minimum clinically viable solutions leveraging Machine Learning (ML) and evolutionary algorithms, for the first …
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Modern lightweight approach for design and implementation of workflow-based clinical guidance system
… healthcare practitioners have adopted the use of clinical decision support systems (CDSS) into their workflow in the past decades. However, there are still many existing challenges for developing a successful CDSS. We propose an XState-React-Redux framework for the design and development of …
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STDMn+p0: a multidimensional patient oriented data mining framework for critical care research
… the ability to create patient characteristic clinical rules. Further defining NICU algorithms, through the extended use of attributes to include gender and GA, and using these new algorithms in clinical decision support systems increases the accuracy and thereby minimizes the risk of adverse …
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A big data and online health analytics framework extended to integrate clinical and countermeasure decision support
… frameworks that utilize big data analytics to support Clinical Decision Support Systems (CDSS) have proven to impact human lives in applications on Earth and in space. In the application of Space Medicine Decision Support Systems (SMDSS) on ISS missions and future space missions to the Moon and …
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Improving Medication Safety by Reducing Miscellaneous Orders Placed via CPOE
… in Northern California and the theme of this clinical nurse leader (CNL) project. “Improving Medication Safety by Reducing Miscellaneous Orders Placed via CPOE” aims to reduce the incidence of medication orders which bypass safety mechanisms when entered incorrectly in the computerized …
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Design of a goal ontology for medical decision-support
… of medical knowledge and reasoning to design decision-support systems. Until now, these efforts have focused primarily on representing content of clinical guidelines and their logical structure. The present study aims to develop a computable representation of health-care providers' intentions …
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AI in the Cath Lab: Implications of Clinical AI-Enabled Assistance for Intravascular Ultrasound Procedures
Clinical decision support tools enabled by artificial intelligence (AI) are entering the medical field slowly, emerging into a space not yet fully regulated by the FDA and with unclear impacts to both medical professionals and patients. Early AI-based clinical decision support systems in healthcare …
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Medication recommendations vs. peer practice in pediatric levothyroxine dosing : a study of collective intelligence from a clinical data warehouse as a potential model for clinical decision support
Clinical decision support systems (CDSS) are developed primarily from knowledge gleaned from evidence-based research, guidelines, trusted resources and domain experts. While these resources generally represent information that is research proven, time-tested and consistent with current medical …
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A clinician-mediated, longitudinal tracking system for the follow-up of clinical results
… to follow-up on abnormal tests is a common clinical concern comprising the quality of care. Although many clinicians track their patient follow-up by scheduling follow-up visits or by leaving physical reminders, most feel that automated, computerized systems to track abnormal test results …
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Multimodal AI for Hospital Readmission Prediction Among Older Adults
… hospitalisation to enhance risk assessment and clinical decision-making. By integrating multiple data sources, this approach improves predictive accuracy and provides deeper insights into the key factors driving readmissions, making AI models more informed and interpretable by using the most …
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Utilization of a transitional care team for medication reconciliation in geriatric primary care
… of computerized provider order entry (CPOE) and clinical decision support systems (CDSS), medication discrepancies are still problematic today. There is substantial evidence available to demonstrate the benefits of using a transition of care (TOC) team for timely, appropriate medication …
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Causal Inference and Evidence-Grounded Language Models for Trustworthy Personalized Clinical Decision Support
Clinical decision support systems (CDSS) are evolving from passive predictive tools into active collaborators in clinical reasoning. However, most machine learning approaches remain limited to risk prediction, lacking the causal reasoning, patient-specific personalization, and evidence-verifiable …
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Deep Learning-Based Brain Tumour Detection and Classification
… now offer a non- invasive alternative capable of supporting radiologists in interpreting MRI scans more efficiently and consistently. It is important to emphasize that AI-based brain tumour detection systems are not intended to replace radiologists or act as autonomous diagnostic tools. Rather, …
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Clinician Decision Support Dashboard: Extracting value from Electronic Medical Records
… EMRs of other patients. The aim of the Clinician Decision Support (CDS) Dashboard is to provide interactive, automated, actionable EMR text-mining tools that help improve both the patient and clinical care staff experience. The CDS Dashboard, in a secure network, helps physicians find …
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A decision support system for predicting the complications of diabetes mellitus: A design science research approach
Health information systems (HIS) serve as the cornerstone of modern healthcare, seamlessly weaving data into actionable insights and empowering professionals to make informed decisions and elevate patient care. Decision support systems became a prominent research area in the discipline of HIS, …
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