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Articles 1 - 7 of 7
Full-Text Articles in Library and Information Science
Clinical Information Extraction From Unstructured Free-Texts, Mingzhe Tao
Clinical Information Extraction From Unstructured Free-Texts, Mingzhe Tao
Legacy Theses & Dissertations (2009 - 2024)
Information extraction (IE) is a fundamental component of natural language processing (NLP) that provides a deeper understanding of the texts. In the clinical domain, documents prepared by medical experts (e.g., discharge summaries, drug labels, medical history records) contain a significant amount of clinically-relevant information that is crucial to the overall well-being of patients. Unfortunately, in many cases, clinically-relevant information is presented in an unstructured format, predominantly consisting of free-texts, making it inaccessible to computerized methods. Automatic extraction of this information can improve accessibility. However, the presence of synonymous expressions, medical acronyms, misspellings, negated phrases, and ambiguous terminologies make automatic extraction …
Bayesian Model Testing Of Models For Ellipsoidal Variation On Stars Due To Hot Jupiters, Anthony Gai
Bayesian Model Testing Of Models For Ellipsoidal Variation On Stars Due To Hot Jupiters, Anthony Gai
Legacy Theses & Dissertations (2009 - 2024)
A massive planet closely orbiting its host star creates tidal forces that distort the typically spherical stellar surface. These distortions, known as ellipsoidal variations, result in variations in the photometric flux emitted by the star, which can be detected by the Kepler Space Telescope. Currently, there exist several models describing such variations and their effect on the photometric fux [1] [2] [3] [4]. By using Bayesian model testing in conjunction with the Bayesian-based exoplanet characterization software package EXONEST [4] [5] [6], the most probable representation for ellipsoidal variations was determined for synthetic data and two systems with confirmed hot Jupiter …
Time Will Tell : Temporal Reasoning In Clinical Narratives And Beyond, Weiyi Sun
Time Will Tell : Temporal Reasoning In Clinical Narratives And Beyond, Weiyi Sun
Legacy Theses & Dissertations (2009 - 2024)
Temporal reasoning in natural language refers to the extraction and understanding of time-related information conveyed in free text. A clinical narrative temporal reasoning component can enable a spectrum of medical natural language processing (NLP) applications that directly improve patient care documentation efficiency, accessibility and accountability. This dissertation contributes in three subtasks under temporal reasoning: temporal annotation, temporal expression extraction and temporal relation inferences. The temporal annotation work described in the dissertation produced one of the first publicly available clinical narratives. We published one of the first sets of temporal
Exploratory Study Of Student Instructional Choice In Online Learning, Andrew Hurd
Exploratory Study Of Student Instructional Choice In Online Learning, Andrew Hurd
Legacy Theses & Dissertations (2009 - 2024)
This exploratory study considers choice theory, decision theory, and the constructivist theory of education to explore college-level computer science learners' behavior when presented with multiple instructional modes (instructional methods for the presentation of course content, such as video, text, audio, animation, etc.) in an online learning environment.
Modeling For Policy Change : A Feedback Perspective On Improving The Effectiveness Of Coastal And Marine Management, Donald David Robadue Jr.
Modeling For Policy Change : A Feedback Perspective On Improving The Effectiveness Of Coastal And Marine Management, Donald David Robadue Jr.
Legacy Theses & Dissertations (2009 - 2024)
Those advocating for effective management of the use of coastal areas and ecosystems have long aspired for an approach to governance that includes information systems with the capability to predict the end results of various courses of action, monitor the impacts of decisions and compare results with those predicted by computer models in order to suggest alterations in the actions needed if the goals are not being achieved. This dissertation draws on system dynamics modeling, content analysis and professional experience to explore four decades of experience in the United States as well as international cases to reveal lessons and strategies …
Toward A Policy Framework For The Design Of Economic Information Packages, Andrew Whitmore
Toward A Policy Framework For The Design Of Economic Information Packages, Andrew Whitmore
Legacy Theses & Dissertations (2009 - 2024)
The emergence of product certifications such as "organic," "fair trade" and "shade grown" has gone far to introduce non-price related product information back into the consumer decision making process thereby reducing information asymmetries and improving market outcomes. Recently, these certifications have been supplemented by the emergence of several web-based consumer decision support systems that are designed to disseminate non-price product information to consumers. Like printed product labels, these new web-based systems present the same informational cues to each consumer regardless of his or her preference for the information and they rate products with fixed weights that are not customized to …
Toward A Theory-Based Natural Language Capability In Robots And Other Embodied Agents : Evaluating Hausser's Slim Theory And Database Semantics, Robin Kowalchuk Burk
Toward A Theory-Based Natural Language Capability In Robots And Other Embodied Agents : Evaluating Hausser's Slim Theory And Database Semantics, Robin Kowalchuk Burk
Legacy Theses & Dissertations (2009 - 2024)
Computational natural language understanding and generation have been a goal of artificial intelligence since McCarthy, Minsky, Rochester and Shannon first proposed to spend the summer of 1956 studying this and related problems. Although statistical approaches dominate current natural language applications, two current research trends bring renewed focus on this goal. The nascent field of artificial general intelligence (AGI) seeks to evolve intelligent agents whose multi-subagent architectures are motivated by neuroscience insights into the modular functional structure of the brain and by cognitive science insights into human learning processes. Rapid advances in cognitive robotics also entail multi-agent software architectures that attempt …