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Articles 1 - 8 of 8
Full-Text Articles in Business
Evaluating Online Health Information: Beyond Readability Formulas, Gondy Leroy, Stephen Helmreich, James Cowie, Trudi Miller '08, Wei Zheng '08
Evaluating Online Health Information: Beyond Readability Formulas, Gondy Leroy, Stephen Helmreich, James Cowie, Trudi Miller '08, Wei Zheng '08
CGU Faculty Publications and Research
Although understanding health information is important, the texts provided are often difficult to understand. There are formulas to measure readability levels, but there is little understanding of how linguistic structures contribute to these difficulties. We are developing a toolkit of linguistic metrics that are validated with representative users and can be measured automatically. In this study, we provide an overview of our corpus and how readability differs by topic and source. We compare two documents for three groups of linguistic metrics. We report on a user study evaluating one of the differentiating metrics: the percentage of function words in a …
Dynamic Generation Of A Table Of Contents With Consumer-Friendly Labels, Trudi Miller '08, Gondy Leroy, Elizabeth Wood
Dynamic Generation Of A Table Of Contents With Consumer-Friendly Labels, Trudi Miller '08, Gondy Leroy, Elizabeth Wood
CGU Faculty Publications and Research
Consumers increasingly look to the Internet for health information, but available resources are too difficult for the majority to understand. Interactive tables of contents (TOC) can help consumers access health information by providing an easy to understand structure. Using natural language processing and the Unified Medical Language System (UMLS), we have automatically generated TOCs for consumer health information. The TOC are categorized according to consumer-friendly labels for the UMLS semantic types and semantic groups. Categorizing phrases by semantic types is significantly more correct and relevant. Greater correctness and relevance was achieved with documents that are difficult to read than with …
Health Information Text Characteristics, Gondy Leroy, Evren Eryilmaz '11, Benjamin T. Laroya
Health Information Text Characteristics, Gondy Leroy, Evren Eryilmaz '11, Benjamin T. Laroya
CGU Faculty Publications and Research
Millions of people search online for medical text, but these texts are often too complicated to understand. Readability evaluations are mostly based on surface metrics such as character or words counts and sentence syntax, but content is ignored. We compared four types of documents, easy and difficult WebMD documents, patient blogs, and patient educational material, for surface and content-based metrics. The documents differed significantly in reading grade levels and vocabulary used. WebMD pages with high readability also used terminology that was more consumer-friendly. Moreover, difficult documents are harder to understand due to their grammar and word choice and because they …
Using A Digital Library Of Images For Communication: Comparison Of A Card-Based System To Pda Software, Trudi Miller '08, Gondy Leroy, John Huang '05, Serena Chuang '05
Using A Digital Library Of Images For Communication: Comparison Of A Card-Based System To Pda Software, Trudi Miller '08, Gondy Leroy, John Huang '05, Serena Chuang '05
CGU Faculty Publications and Research
Autism spectrum disorder has become one of the most prevalent developmental disorders and one of the main impairments is difficulty with communication. One method of augmentative and alternative communication is the use of the Picture Exchange Communication System (PECS) to create messages using a series of images printed on cards and organized in binders. We are developing a digital alternative based on an image library that is displayed on a personal digital assistant (PDA). We conducted an initial user acceptance study that compared the effectiveness and usability of both systems. The study showed that the PDA system was able to …
Genescene: Biomedical Text And Data Mining, Gondy Leroy, Hsinchun Chen, Jesse D. Martinez, Shauna Eggers, Ryan R. Falsey, Kerri L. Kislin, Zan Huang, Jiexun Li, Jie Xu, Daniel M. Mcdonald, Gavin Ng
Genescene: Biomedical Text And Data Mining, Gondy Leroy, Hsinchun Chen, Jesse D. Martinez, Shauna Eggers, Ryan R. Falsey, Kerri L. Kislin, Zan Huang, Jiexun Li, Jie Xu, Daniel M. Mcdonald, Gavin Ng
CGU Faculty Publications and Research
To access the content of digital texts efficiently, it is necessary to provide more sophisticated access than keyword based searching. GeneScene provides biomedical researchers with research findings and background relations automatically extracted from text and experimental data. These provide a more detailed overview of the information available. The extracted relations were evaluated by qualified researchers and are precise. A qualitative ongoing evaluation of the current online interface indicates that this method to search the literature is more useful and efficient than keyword based searching.
Medtextus: An Ontology-Enhanced Medical Portal, Gondy Leroy, Hsinchun Chen
Medtextus: An Ontology-Enhanced Medical Portal, Gondy Leroy, Hsinchun Chen
CGU Faculty Publications and Research
In this paper we describe MedTextus, an online medical search portal with dynamic search and browse tools. To search for information, MedTextus lets users request synonyms and related terms specifically tailored to their query. A mapping algorithm dynamically builds the query context based on the UMLS ontology and then selects thesaurus terms that fit this context. Users can add these terms to their query and meta-search five medical databases. To facilitate browsing, the search results can be reviewed as a list of documents per database, as a set of folders into which all the documents are automatically categorized based on …
Filling Preposition-Based Templates To Capture Information From Medical Abstracts, Gondy Leroy, Hsinchun Chen
Filling Preposition-Based Templates To Capture Information From Medical Abstracts, Gondy Leroy, Hsinchun Chen
CGU Faculty Publications and Research
Due to the recent explosion of information in the biomedical field, it is hard for a single researcher to review the complex network involving genes, proteins, and interactions. We are currently building GeneScene, a toolkit that will assist researchers in reviewing existing literature, and report on the first phase in our development effort: extracting the relevant information from medical abstracts. We are developing a medical parser that extracts information, fills basic prepositional-based templates, and combines the templates to capture the underlying sentence logic. We tested our parser on 50 unseen abstracts and found that it extracted 246 templates with a …
Customizable And Ontology-Enhanced Medical Information Retrieval Interfaces, Gondy Leroy, K.M. Tolle, Hsinchun Chen
Customizable And Ontology-Enhanced Medical Information Retrieval Interfaces, Gondy Leroy, K.M. Tolle, Hsinchun Chen
CGU Faculty Publications and Research
This paper describes the development and testing of the Medical Concept Mapper as an aid to providing synonyms and semantically related concepts to improve searching. All terms are related to the userquery and fit into the query context. The system is unique because its five components combine humancreated and computer-generated elements. The Arizona Noun Phraser extracts phrases from natural language user queries. WordNet and the UMLS Metathesaurus provide synonyms. The Arizona Concept Space generates conceptually related terms. Semantic relationships between queries and concepts are established using the UMLS Semantic Net. Two user studies conducted to evaluate the system are described.