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Knowledge-Enabled Entity Extraction, Hussein S. Al-Olimat
Knowledge-Enabled Entity Extraction, Hussein S. Al-Olimat
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Information Extraction (IE) techniques are developed to extract entities, relationships, and other detailed information from unstructured text. The majority of the methods in the literature focus on designing supervised machine learning techniques, which are not very practical due to the high cost of obtaining annotations and the difficulty in creating high quality (in terms of reliability and coverage) gold standard. Therefore, semi-supervised and distantly-supervised techniques are getting more traction lately to overcome some of the challenges, such as bootstrapping the learning quickly. This dissertation focuses on information extraction, and in particular entities, i.e., Named Entity Recognition (NER), from multiple domains, …
Agent-Based Simulation Of Artificial-Intelligence-Assisted Transfer Of Care, Paul B. Stone
Agent-Based Simulation Of Artificial-Intelligence-Assisted Transfer Of Care, Paul B. Stone
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This study demonstrates the application of Agent-Based Simulation as a potential training aid for Transfer of Care (ToC) between EMS and a hospital triage department. The specific aim was to develop a simulation to increase the efficiency and accountability of information communication during ToC to test the suitability of Agent-Based Simulation to address training requirements in complex, health provision settings. This paper focuses on the design of the training simulation, including the development of individual agents within the simulation through the user interface elements and the evaluation and verification of the prototype simulator. The primary objective is for the simulation …