Browsing by Author "Kuo, Kevin"
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Item Artificially Intelligent Medical Assistant Robot (AIMAR)(2020) Ronin, Dana; Horne, Nina; Daniel, Paulos; Jacobson, Ben; Kuo, Kevin; Marsandi, Michelle; Offenberg, Natalie; Utz, Ryan; Vandergriff, Johan; Deane, AnilHealthcare providers face financial, regulatory, and logistical obstacles in supplying quality care. Applying robotics and artificial intelligence (AI) to healthcare reduces demands on providers, increases accuracy by supplementing medical diagnoses, and improves patient outcomes. Team AIMAR (Artificially Intelligent Medical Assistant Robot) has constructed a modular robotic healthcare AI system, consisting of advanced diagnostic features as supplements to a generic base. The team focused on analyzing images with machine learning to identify skin conditions. The base robot can move around the home or hospital, pick up objects, and interact with patients and doctors. The patient can log in using face authentication so that patient data is secure, and interact verbally and visually through the user interface. New features can easily be added to the base robot's existing integrated features, making AIMAR adaptable for many desired contexts.Item Artificially Intelligent Medical Assistant Robot: Automating Data Collection and Diagnostics for Medical Practitioners(2021) Daniel, Paulos; Horne, Nina; Kuo, Kevin; Marsandi, Michelle; Offenberg, Natalie; Ronin, Dana; Utz, Ryan; Vandegriff, Johan; Deane, AnilHealthcare providers face financial, regulatory, and logistical obstacles in supplying quality care. A robotic system can improve patient outcomes and reduce demands on providers by automating data collection and supplementing medical diagnoses. Team AIMAR (Artificially Intelligent Medical Assistant Robot) constructed such a system focusing on three core features: natural language interaction, computer vision, and mobility. Thus, in addition to developing a robotic base with navigational and conversational abilities, Team AIMAR implemented two prototype modules: a skin lesion image classifier and a medical chatbot. Additionally, Team AIMAR created a framework to test and assess the functionality of the fully integrated system in a simulated environment. Several directions exist for future work, including expanding the user interface, improving navigation and sensing capabilities, communicating with electronic health record systems, and the integration of a physical arm.Item Implementing the “Enhancing Music Addressability” API for MusicXML(2020) Kuo, Kevin; Viglianti, RaffaeleThe ability to “address” areas of a musical score is useful in music scholarship such as analysis and/or historical research.In this project, we implement software that enables us to “select” regions of MusicXML files, in accordance with the Enhancing Music Addressability (EMA) specification.