University of Texas at Austin

About: University of Texas at Austin is a education organization based out in Austin, Texas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 94352 authors who have published 206297 publications receiving 9070052 citations. The organization is also known as: UT-Austin & UT Austin.

ACR Thyroid Imaging, Reporting and Data System (TI-RADS): White Paper of the ACR TI-RADS Committee

Abstract: Thyroid nodules are a frequent finding on neck sonography. Most nodules are benign; therefore, many nodules are biopsied to identify the small number that are malignant or require surgery for a definitive diagnosis. Since 2009, many professional societies and investigators have proposed ultrasound-based risk stratification systems to identify nodules that warrant biopsy or sonographic follow-up. Because some of these systems were founded on the BI-RADS® classification that is widely used in breast imaging, their authors chose to apply the acronym TI-RADS, for Thyroid Imaging, Reporting and Data System. In 2012, the ACR convened committees to (1) provide recommendations for reporting incidental thyroid nodules, (2) develop a set of standard terms (lexicon) for ultrasound reporting, and (3) propose a TI-RADS on the basis of the lexicon. The committees published the results of the first two efforts in 2015. In this article, the authors present the ACR TI-RADS Committee's recommendations, which provide guidance regarding management of thyroid nodules on the basis of their ultrasound appearance. The authors also describe the committee's future directions.

Content-Based Book Recommending Using Learning for Text Categorization

Abstract: Recommender systems improve access to relevant products and information by making personalized suggestions based on previous examples of a user's likes and dislikes. Most existing recommender systems use social filtering methods that base recommendations on other users' preferences. By contrast, content-based methods use information about an item itself to make suggestions. This approach has the advantage of being able to recommended previously unrated items to users with unique interests and to provide explanations for its recommendations. We describe a content-based book recommending system that utilizes information extraction and a machine-learning algorithm for text categorization. Initial experimental results demonstrate that this approach can produce accurate recommendations.

Characterization of the LIGO detectors during their sixth science run

Abstract: In 2009–2010, the Laser Interferometer Gravitational-Wave Observatory (LIGO) operated together with international partners Virgo and GEO600 as a network to search for gravitational waves (GWs) of astrophysical origin. The sensitivity of these detectors was limited by a combination of noise sources inherent to the instrumental design and its environment, often localized in time or frequency, that couple into the GW readout. Here we review the performance of the LIGO instruments during this epoch, the work done to characterize the detectors and their data, and the effect that transient and continuous noise artefacts have on the sensitivity of LIGO to a variety of astrophysical sources.

Information Technologies and Business Value: An Analytic and Empirical Investigation

Abstract: An important management question today is whether the anticipated economic benefits of Information Technology IT are being realized. In this paper, we consider this problem to be measurement related, and propose and test a new process-oriented methodology for ex post measurement to audit IT impacts on a strategic business unit SBU or profit center's performance. The IT impacts on a given SBU are measured relative to a group of SBUs in the industry. The methodology involves a two-stage analysis of intermediate and higher level output variables that also accounts for industry and economy wide exogenous variables for tracing and measuring IT contributions. The data for testing the proposed model were obtained from SBUs in the manufacturing sector. Our results show significant positive impacts of IT at the intermediate level. The theoretical contribution of the study is a methodology that attempts to circumvent some of the measurement problems in this domain. It also provides a practical management tool to address the question of why or why not certain IT impacts occur. Additionally, through its process orientation, the suggested approach highlights key variables that may require managerial attention and subsequent action.