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 9 of 9 for “"Healthcare AI"”.
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Systematic Development of Healthcare AI: From Data Curation, Algorithm Optimization, Benchmark Design and Clinical Applications
Artificial intelligence (AI) has brought transformative changes to healthcare industry in the recent years from various aspects, such as patient care, disease diagnosis and medical research. As healthcare systems worldwide face increasing pressure from aging populations and rising chronic disease …
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Medical Professionals' Perceptions of Healthcare Artificial Intelligence
… show differences in their perceptions of healthcare artificial intelligence (AI). Specifically, the researcher hypothesized that participants with more expertise and experience would have greater negative perceptions associated with AI in healthcare compared to participants with a lower …
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Healthcare Agents: Large Language Models in Health Prediction and Decision-Making
Large Language Models (LLMs) are transforming healthcare, yet utilizing them for clinical applications presents significant challenges. In this thesis, we explore two critical aspects in healthcare AI: (1) leveraging LLMs for multimodal health prediction from wearable sensor data and (2) developing …
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Impact of personalization on businesses and their stakeholders
Personalization — the tailoring of products, services, and interactions to individual users through data-driven models and algorithmic decision-making — has become a strategic axis for contemporary European firms, promising enhanced engagement, increased efficiency, and new pathways for value …
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Needs-driven, utility-oriented, standards-based operationalization of artificial intelligence for clinical decision support: a framework with application to suicide prevention
While artificial intelligence (AI) technologies increasingly permeate our daily lives, the adoption and impact of AI have fallen short of expectations in healthcare. The challenges of operationalizing AI in healthcare are complex and include interaction design (e.g. poorly designed user …
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Bridging the Gap: From Artificial Intelligence and Optimization Theory to Action
… Research (OR) and Artificial Intelligence (AI), a persistent gap remains between these developments and their practical implementation in real-world settings. Despite significant progress in these fields, many OR and ML approaches struggle to scale to realistic problem sizes, lack robustness …
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Natural Language Foundation Models in Medical Artificial Intelligence
… experts across diverse fields, including healthcare, to think deeply about how artificial intelligence (AI) can revolutionize their fields. In this time, general foundation models, rather than narrow and highly specialized task-specific systems, have begun to emerge as the dominant …
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TRUST: Clinical Text Retrieval and Use towards Scientific Rigor and Transparent Process
… research into practice, and has facilitated healthcare decision-making through enabling accurate and timely supply of health information. Leveraging this supply of information, the Institute of Medicine envisioned the concept of continuously Learning Health Systems (LHS) in 2007, with the aim …
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AI-Serve: Empowering Service Provisioning with Conversational and Generative AI
The global conversational AI market has been growing rapidly with widely adopted applications in diverse domains, including customer service, finance, education, and healthcare. Voice-enabled assistants such as Siri, Alexa, and Google Assistant are used by hundreds of millions of people worldwide …