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.
Results
Showing 1 to 11 of 11 for “"AI in Healthcare"”.
-
Interpretable and Automated Bias Detection for AI in Healthcare
Biases in artificial intelligence systems and the data they operate over are a major hurdle to their application in clinical and biomedical settings. Such systems have frequently been shown to fail to generalize from their training data to the real world environment and often display differing …
-
Technology-Driven Solutions for Smarter Care: Telemedicine, Data-Driven Analytics, and AI in Healthcare Operations
Healthcare systems globally are grappling with increasing demand, ageing populations, and persistent resource constraints. In the United Kingdom, the National Health Service (NHS), a publicly funded system offering free care at the point of use, is facing mounting pressure from long outpatient …
-
Advancing Healthcare with GenerativeAI: A Multifaceted Approach to Reliable Medical Information and Innovation
The rapid advancements in Artificial Intelligence (AI) have transformed the healthcare industry, reshaping the way we approach patient care, medical research, and healthcare delivery. This thesis explores the journey of AI in healthcare, from its early beginnings to the current landscape of highly …
-
The Influence of AI-Literate Leadership on AI Adoption in Healthcare Organizations
<p>The adoption of Artificial Intelligence (AI) in healthcare has the potential to revolutionize patient care, optimize operations, and advance diagnostic precision. However, successful adoption depends on AI-literate leadership capable of addressing ethical, technical, and organizational …
-
Medical Professionals' Perceptions of Healthcare Artificial Intelligence
<p>This study examined whether medical professionals across different levels of expertise 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 …
-
Practical Considerations For the Deployment of Clinical NLP Systems
Although recent advances in scaling large language models (LLMs) have resulted in improvements on many NLP tasks, it remains unclear whether these models trained primarily with general web text are the right tool in highly specialized, safety critical domains such as healthcare. A healthcare system …
-
Representation Learning for Patients in the Intensive Care Unit
The past decade has seen accelerating interest in Artificial Intelligence (AI) in Healthcare. Data is now being generated in the form of Electronic Health Records at a scale previously unimaginable. Not only does this create opportunities for the application of AI, but it also drives innovation in …
-
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 …
-
IMPROVING PATIENT EXPERIENCE WITH EMOTION-SENSITIVE LARGE MODELS
In the contemporary digital healthcare landscape, technological innovations have significantly improved access and efficiency; yet, an essential question persists: can these technologies also address the emotional needs of patients? This study investigates the role of Large Language Models (LLMs), …
-
Towards Interpretable AI for Longitudinal Disease Monitoring and Clinical Reporting from Chest X-Rays
Chest radiography (CXR) plays a pivotal role in diagnostic imaging for monitoring disease progression and evaluating treatment effectiveness. Despite notable advancements in machine learning, disease progression monitoring remains relatively underexplored. Challenges arise from the specificity of …
-
Multimodal AI Tools for Predicting Neurological and Neurodevelopmental Trajectories
… è presente nell'allegato / the abstract is in the attachment