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The Unified Medical Language System (UMLS) is an important terminological system. By the policy of its curators, each concept of the UMLS should be assigned the most specific Semantic Types (STs) in the UMLS Semantic Network (SN). Hence, the Semantic Types of most UMLS concepts are assigned at or near the bottom (leaves) of the UMLS Semantic Network. While most ST assignments are correct, some errors...
The Gene hierarchy of the National Cancer Institute (NCI) Thesaurus (NCIt) is of high priority for NCI. It is important to have quality assurance (QA) techniques to improve its content quality. We present a two-step methodology concentrating on auditing the modeling of complex concepts, which are shown to have a higher error rate compared to control concepts. In the first step, we test whether concepts...
Big Knowledge repositories, in the form of large ontologies, typically consist of many thousands of knowledge assertions. They have complex network structures consisting of nodes and links. Without some form of comprehension, humans cannot make correct, innovative and creative use of Big Knowledge. Visualization is an important tool for knowledge comprehension, however, the node-link diagrams become...
Prescription drug abuse is one of the fastest growing public health problems in the USA. To address this epidemic, a near real-time monitoring strategy, instead of one resorting to a retrospective health records, may improve detecting the prevalence and patterns of abuse of both illegal drugs and prescription medications. In this paper, our primary goals are to demonstrate the possibility of utilizing...
In this system prototype demonstration we present, Ultimate Course Search (UCS), a learning tool developed to provide students ways to efficiently search electronic educational materials. UCS integrates slides, lecture videos and textbooks into a single platform. The keywords extracted from the textbooks and the slides are the basis of the indexing scheme. For the videos, UCS relies on slide transitions...
Many patients suffer from comorbidity conditions; for example, obese patients often develop type-2 diabetes and hypertension. In the U.S., 80% of Medicare spending is for managing patients with these multiple coexisting conditions. Predicting potential comorbidity conditions for an individual patient can promote preventive care and reduce costs. Predicting possible comorbidity progression paths can...
In the U.S., 80% of Medicare spending is for managing patients with multiple coexisting conditions. Predicting potentially correlated diseases for an individual patient and correlated disease progression paths are both important research tasks. For example, obese patients are at an increased risk for developing type-2 diabetes and hypertension. This correlation is called comorbidity relationship....
Terminologies are typically large and complex knowledge systems. It is difficult to obtain an orientation into their structure and content. In previous research we designed compact summary networks called partial-area taxonomies to provide a structural summary of a terminology. The sizes of a terminology and of its partial-area taxonomy are defined as their numbers of nodes. While a partial-area taxonomy...
An important task of public health officials is to keep track of spreading epidemics, and the locations and speed with which they appear. Furthermore, there is interest in understanding how concerned the population is about a disease outbreak. Twitter can serve as an important data source to provide this information in real time. In this paper, we focus on sentiment classification of Twitter messages...
Developing a domain ontology with concepts and relationships between them is a challenge, since knowledge engineering is a labor intensive process that can be a bottleneck and is often not scalable. Developing a cyber-security ontology is no exception. A security ontology can improve search for security learning resources that are scattered in different locations in different formats, since it can...
Modern search engines provide users with suggested query completions. These search suggestions are often ambiguous in nature and could refer to any number of homonyms. Previously we used a static ontology built from data in Wikipedia to address this issue. Here, we present a method for dynamically building an ontology of "famous people" based on mining the suggested completions of a search...
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