Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Jake Vasilakes"'
Autor:
Xing He, Rui Zhang, Rubina Rizvi, Jake Vasilakes, Xi Yang, Yi Guo, Zhe He, Mattia Prosperi, Jinhai Huo, Jordan Alpert, Jiang Bian
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 19, Iss S4, Pp 1-18 (2019)
Abstract Background Dietary supplements (DSs) are widely used. However, consumers know little about the safety and efficacy of DSs. There is a growing interest in accessing health information online; however, health information, especially online inf
Externí odkaz:
https://doaj.org/article/9b83c9b5667e4309a69472883ce10f22
Publikováno v:
Journal of Biomedical Informatics. 141:104347
Autor:
Olivier Bodenreider, Anusha Bompelli, Jake Vasilakes, Terrence J. Adam, Rui Zhang, Jeffrey R. Bishop
Publikováno v:
J Am Med Inform Assoc
Objective We sought to assess the need for additional coverage of dietary supplements (DS) in the Unified Medical Language System (UMLS) by investigating (1) the overlap between the integrated DIetary Supplements Knowledge base (iDISK) DS ingredient
Autor:
Cui Tao, Rubina F. Rizvi, Rui Zhang, Jeffrey R. Bishop, Genevieve B. Melton, Jake Vasilakes, Terrence J. Adam, Jian-Guo Bian
Publikováno v:
J Am Med Inform Assoc
Objective To build a knowledge base of dietary supplement (DS) information, called the integrated DIetary Supplement Knowledge base (iDISK), which integrates and standardizes DS-related information from 4 existing resources. Materials and Methods iDI
Publikováno v:
Vasilakes, J, Zerva, C, Miwa, M & Ananiadou, S 2022, ' Learning Disentangled Representations of Negation and Uncertainty. ', pp. 8380–8397 . < https://aclanthology.org/2022.acl-long.574.pdf >
University of Manchester-PURE
University of Manchester-PURE
Negation and uncertainty modeling are long-standing tasks in natural language processing. Linguistic theory postulates that expressions of negation and uncertainty are semantically independent from each other and the content they modify. However, pre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2bb471ec4b11cddc5d17c13d2743a251
Discovering novel drug-supplement interactions using SuppKG generated from the biomedical literature
Autor:
Dalton Schutte, Jake Vasilakes, Anu Bompelli, Yuqi Zhou, Marcelo Fiszman, Hua Xu, Halil Kilicoglu, Jeffrey R. Bishop, Terrence Adam, Rui Zhang
Publikováno v:
Journal of biomedical informatics. 131
Develop a novel methodology to create a comprehensive knowledge graph (SuppKG) to represent a domain with limited coverage in the Unified Medical Language System (UMLS), specifically dietary supplement (DS) information for discovering drug-supplement
Autor:
Aaron D. Aguirre, Mouaz H. Al-Mallah, Jamal Al Ani, Subhi J. Al’Aref, Ahmed M. Altibi, Leon Axel, Andrea Baggiano, Lohendran Baskaran, Jan-Walter Benjamins, Laura J. Brattain, Qi Chang, Gloria Cicala, Kristin M. Corey, Jessica De Freitas, Damini Dey, Abdallah Elshafeey, Mohamed B. Elshazly, Laura Fusini, Benjamin S. Glicksberg, Andrea I. Guaricci, Marco Guglielmo, Donghee Han, Kipp W. Johnson, Luis Eduardo Juarez-Orozco, Mohammad Kachuee, Aman Kansal, Sehj Kashyap, Felix Y.J. Keng, Shaden Khalaf, Pegah Khosravi, Attila Kovács, Viksit Kumar, Benjamin C. Lee, Andrew Lin, Pál Maurovich-Horvat, Dimitris N. Metaxas, Omar Mhaimeed, Riccardo Miotto, Giuseppe Muscogiuri, Aziz Nazha, Gianluca Pontone, Mark Rabbat, Mark G. Rabbat, Nathan Radakovich, Mina Rezaei, Francesca Ricci, Anthony E. Samir, Majid Sarrafzadeh, Alpana Senapati, Mark Sendak, Piotr J. Slomka, Emily Tat, Brian A. Telfer, Márton Tokodi, Pim van der Harst, Jake Vasilakes, Ming Wai Yeung, Rui Zhang, Sicheng Zhou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0d451e345ad3aa30de996eb9f4cb7743
https://doi.org/10.1016/b978-0-12-820273-9.01002-2
https://doi.org/10.1016/b978-0-12-820273-9.01002-2
Autor:
Jake Vasilakes, Anusha Bompelli, Rui Zhang, Benjamin C. Knoll, Serguei V. S. Pakhomov, Greg M. Silverman, Raymond L. Finzel
Publikováno v:
Artificial Intelligence in Medicine ISBN: 9783030591366
AIME
AIME
Natural Language Processing (NLP) techniques have been used extensively to extract concepts from unstructured clinical trial eligibility criteria. Recruiting patients whose information in Electronic Health Records matches clinical trial eligibility c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::805fb7961f7241c024b42b2a0ae534ec
https://doi.org/10.1007/978-3-030-59137-3_7
https://doi.org/10.1007/978-3-030-59137-3_7
Autor:
Mattia Prosperi, Rubina F. Rizvi, Jian-Guo Bian, Xi Yang, Xing He, Jake Vasilakes, Zhe He, Rui Zhang, Yi Guo
Publikováno v:
BIBM
Dietary supplements (DS) are widely consumed. However, most people have limited knowledge about the safety and efficacy of DS. Even though there exists the well-curated integrated DIetary Supplement Knowledge base (iDISK) with a formal knowledge repr
Autor:
Rubina F, Rizvi, Terrence J, Adam, Elizabeth A, Lindemann, Jake, Vasilakes, Serguei Vs, Pakhomov, Jeffrey R, Bishop, Genevieve B, Melton, Rui, Zhang
Publikováno v:
AMIA Summits on Translational Science Proceedings
Dietary supplements, often considered as food, are widely consumed despite of limited knowledge around their safety/efficacy and any well-established regulatory policies, unlike their drug counterparts. Informatics methods may be useful in filling th