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311 results on '"Mostafa, Javed"'

1. Automated Compliance Analysis on Clinical Notes to Improve Cancer Lifestyle Management

Author

Hou, Yujia, Mostafa, Javed, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Sserwanga, Isaac, editor, Joho, Hideo, editor, Ma, Jie, editor, Hansen, Preben, editor, Wu, Dan, editor, Koizumi, Masanori, editor, and Gilliland, Anne J., editor

Published
2024
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2. Global Undergraduate Research Landscape Analysis and Its Effect on 4th Industrial Revolution

Author

Mostafa, Javed, Ashrafi, Shamim, Ahmed, Kazi Sadman, Islam, Md. Imranul, Chowdhury, Shadman Islam, Khaleque, Muntasir, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Hossain, Sazzad, editor, Hossain, Md. Shahadat, editor, Kaiser, M. Shamim, editor, Majumder, Satya Prasad, editor, and Ray, Kanad, editor

Published
2022
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3. Toward Exploratory Search in Biomedicine: Evaluating Document Clusters by MeSH as a Semantic Anchor

Author

Ortiz, Michael Segundo, Seki, Kazuhiro, and Mostafa, Javed

Subjects
Computer Science - Information Retrieval, Computer Science - Digital Libraries, Computer Science - Human-Computer Interaction
Abstract

The current mode of biomedical literature search is severely limited in effectively finding information relevant to specialists. A potential approach to solving this problem is exploratory search, which allows users to interactively navigate through a vast document collection. As the first step toward exploratory search for specialists in biomedicine, this paper develops a methodology to evaluate quality of document clusters. For this purpose, we incorporate human expertise into data set creation and evaluation framework by leveraging MeSH terms as semantic anchors. In addition, we investigate the benefit of full-text data for improving cluster quality., Comment: This work is currently under consideration for the 17th World Congress of Medical and Health Informatics. Please follow the link for more information - http://www.medinfo-lyon.org/en/about-us/medinfo2019/

Published
2018

4. Understanding Voice Search Behavior: Review and Synthesis of Research

Author

Xing, Zhaopeng, Yuan, Xiaojun, Wu, Dan, Huang, Yeman, Mostafa, Javed, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Stephanidis, Constantine, editor, Kurosu, Masaaki, editor, Degen, Helmut, editor, and Reinerman-Jones, Lauren, editor

Published
2020
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6. Health Data Exchange: A Search Engine to Identify Health Experts.

Author

Ar Rakib, Nibras, Kibria, Mohammad Golam, and Mostafa, Javed

Subjects
SEARCH engines, INFORMATION sharing, INFORMATION retrieval, NATURAL language processing, MEDICAL databases
Abstract

The study proposes and describes a novel system called the Health Data Exchange. HDX is useful for identifying relevant experts in healthcare based on specific skill sets and their cohorts. Initial experience suggests that an expert database based on biographical data can be developed. Several techniques for automatically identifying the critical data, data normalization, storage, and retrieval are described that supported the development of the system. Such a system has the potential to facilitate efficient search and foster global collaboration among healthcare experts. [ABSTRACT FROM AUTHOR]

Published
2024
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8. Implementation of Emergency Medical Text Classifier for syndromic surveillance.

Author

Travers, Debbie, Haas, Stephanie W, Waller, Anna E, Schwartz, Todd A, Mostafa, Javed, Best, Nakia C, and Crouch, John

Subjects
Information and Computing Sciences, Biomedical and Clinical Sciences, Clinical Sciences, Clinical Research, Health Services, Good Health and Well Being, Disease Outbreaks, Electronic Health Records, Emergency Service, Hospital, Humans, Natural Language Processing, Public Health Informatics, Public Health Surveillance
Abstract

Public health officials use syndromic surveillance systems to facilitate early detection and response to infectious disease outbreaks. Emergency department clinical notes are becoming more available for surveillance but present the challenge of accurately extracting concepts from these text data. The purpose of this study was to implement a new system, Emergency Medical Text Classifier (EMT-C), into daily production for syndromic surveillance and evaluate system performance and user satisfaction. The system was designed to meet user preferences for a syndromic classifier that maximized positive predictive value and minimized false positives in order to provide a manageable workload. EMT-C performed better than the baseline system on all metrics and users were slightly more satisfied with it. It is vital to obtain user input and test new systems in the production environment.

Published
2013

11. Identifying Neurological Patterns Associated with Information Seeking: A Pilot fMRI Study

Author

Mostafa, Javed, Carrasco, Vincent, Foster, Chris, Giovenallo, Kelly, Spagnoletti, Paolo, Series editor, De Marco, Marco, Series editor, Pouloudi, Nancy, Series editor, Te'eni, Dov, Series editor, vom Brocke, Jan, Series editor, Winter, Robert, Series editor, Baskerville, Richard, Series editor, Davis, Fred D., editor, Riedl, René, editor, Léger, Pierre-Majorique, editor, and Randolph, Adriane B., editor

Published
2015
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13. Digital Humanities and Information Science: Making A Difference?

Author

de Fremery, Wayne, Mostafa, Javed, Pennington, Diane M. Rasmussen, Terra, Ana Lúcia, Cha, Javier, and Oh, Sam

Subjects
*DIGITAL humanities, *INFORMATION technology, *INFORMATION sharing, *INFORMATION policy, *ARTIFICIAL intelligence, *DIGITAL technology, *INFORMATION science
Abstract

In a 2012 ASIS&T panel titled "Humanistic Information Science," Melanie Feinberg, Jens‐Erik Mai, Jonathan Furner, and Joseph Tennis argued that information science as a field "could be richer" if it were to embrace "humanistic approaches to information science" (Feinberg, Furner, Mai, Tennis, 2012). Approximately a decade later, this panel returns to foundational questions about science, the humanities, and information as a field of study to consider the relationship between the digital humanities and information science. How are information science and the digital humanities different? How are they similar? How might work done in one field make a difference in the another? What might digital humanists and information scientists have to say about translation and the transposition of disciplinary knowledge to and from each respective field? How might the translation and transposition of disciplinary knowledge in the humanities and information science inform practice, policy, and action in both and beyond? This panel will provide a forum for attendees of ASIS&T's 86th Annual Meeting to debate answers with leading information scientists and digital humanists from around the world. [ABSTRACT FROM AUTHOR]

Published
2023
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14. Cohort Identification from Free-Text Clinical Notes Using SNOMED CT’s Hierarchical Semantic Relations

Author

Chang, Eunsuk and Mostafa, Javed

Subjects
Articles
Abstract

In this paper, a new cohort identification system that exploits the semantic hierarchy of SNOMED CT is proposed to overcome the limitations of supervised machine learning-based approaches. Eligibility criteria descriptions and free-text clinical notes from the 2018 National NLP Clinical Challenge (n2c2) were processed to map to relevant SNOMED CT concepts and to measure semantic similarity between the eligibility criteria and patients. The eligibility of a patient was determined if the patient had a similarity score higher than a threshold cut-off value. The performance of the proposed system was evaluated for three eligibility criteria. The performance of the current system exceeded the previously reported results of the 2018 n2c2, achieving the average F1 score of 0.933. This study demonstrated that SNOMED CT alone can be leveraged for cohort identification tasks without referring to external textual sources for training.

Published
2023

17. Image Retrieval for Alzheimer’s Disease Detection

Author

Agarwal, Mayank, Mostafa, Javed, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Caputo, Barbara, editor, Müller, Henning, editor, Syeda-Mahmood, Tanveer, editor, Duncan, James S., editor, Wang, Fei, editor, and Kalpathy-Cramer, Jayashree, editor

Published
2010
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20. Data science curriculum in the iField.

Author

Zhang, Yin, Wu, Dan, Hagen, Loni, Song, Il‐Yeol, Mostafa, Javed, Oh, Sam, Anderson, Theresa, Shah, Chirag, Bishop, Bradley Wade, Hopfgartner, Frank, Eckert, Kai, Federer, Lisa, and Saltz, Jeffrey S.

Subjects
DATA science, COMMITTEES, LEADERSHIP, JOB descriptions, CURRICULUM, UNDERGRADUATE programs, GRADUATE education, DATA analytics, INFORMATION technology, DELPHI method, DATA mining
Abstract

Many disciplines, including the broad Field of Information (iField), offer Data Science (DS) programs. There have been significant efforts exploring an individual discipline's identity and unique contributions to the broader DS education landscape. To advance DS education in the iField, the iSchool Data Science Curriculum Committee (iDSCC) was formed and charged with building and recommending a DS education framework for iSchools. This paper reports on the research process and findings of a series of studies to address important questions: What is the iField identity in the multidisciplinary DS education landscape? What is the status of DS education in iField schools? What knowledge and skills should be included in the core curriculum for iField DS education? What are the jobs available for DS graduates from the iField? What are the differences between graduate‐level and undergraduate‐level DS education? Answers to these questions will not only distinguish an iField approach to DS education but also define critical components of DS curriculum. The results will inform individual DS programs in the iField to develop curriculum to support undergraduate and graduate DS education in their local context. [ABSTRACT FROM AUTHOR]

Published
2023
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21. Data science curriculum in theiField

Author

Zhang, Yin, primary, Wu, Dan, additional, Hagen, Loni, additional, Song, Il‐Yeol, additional, Mostafa, Javed, additional, Oh, Sam, additional, Anderson, Theresa, additional, Shah, Chirag, additional, Bishop, Bradley Wade, additional, Hopfgartner, Frank, additional, Eckert, Kai, additional, Federer, Lisa, additional, and Saltz, Jeffrey S., additional

Published
2022
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47. An experiment in building profiles in information filtering: the role of context of user relevance feedback

Author

Quiroga, Luz M. and Mostafa, Javed

Subjects
Electronic data processing -- Usage, Personal information management systems -- Research, Records management -- Research, Personal information management software, Business, Computers and office automation industries
Abstract

An experiment was conducted to see how relevance feedback could be used to build and adjust profiles to improve the performance of filtering systems. Data was collected during the system interaction of 18 graduate students with SIFTER (Smart Information Filtering Technology for Electronic Resources), a filtering system that ranks incoming information based on users' profiles. The data set came from a collection of 6000 records concerning consumer health. In the first phase of the study, three different modes of profile acquisition were compared. The explicit mode allowed users to directly specify the profile; the implicit mode utilized relevance feedback to create and refine the profile; and the combined mode allowed users to initialize the profile and to continuously refine it using relevance feedback. Filtering performance, measured in terms of Normalized Precision, showed that the three approaches were significantly different ([alpha] = 0.05 and p = 0.012). The explicit mode of profile acquisition consistently produced superior results. Exclusive reliance on relevance feedback in the implicit mode resulted in inferior performance. The low performance obtained by the implicit acquisition mode motivated the second phase of the study, which aimed to clarify the role of context in relevance feedback judgments. An inductive content analysis of thinking aloud protocols showed dimensions that were highly situational, establishing the importance context plays in feedback relevance assessments. Results suggest the need for better representation of documents, profiles, and relevance feedback mechanisms that incorporate dimensions identified in this research. Keywords: Information filtering; Relevance feedback judgments; User models; User profiles

Published
2002

48. Modeling user interest shift using a Bayesian approach

Author

Mostafa, Javed and Lam, Wai

Subjects
Information science -- Research, Bayesian statistical decision theory -- Usage, Information storage and retrieval -- Research, Internet filtering software -- Research, Web sites -- Usage, Searching behavior -- Research, Internet/Web search services -- Technology application, Consumer preferences -- Models, Consumers -- Beliefs, opinions and attitudes, Computers, Library and information science, Mathematics
Abstract

Findings of a study show, in general, that the Bayesian approach is a feasible and effective technique for modeling user interest shift in information filtering systems. Modeling of changes in user interest in information filtering systems has been studied and a new technique for tracking user interest shifts based on a Bayesian approach developed. . Relationships between cost of detection error, degree of shift, and time needed for detection are studied.

Published
2001

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