Zobrazeno 1 - 10
of 84
pro vyhledávání: '"Serguei V. S. Pakhomov"'
Autor:
Rui Zhang, Serguei V. S. Pakhomov, Elliot G. Arsoniadis, Janet T. Lee, Yan Wang, Genevieve B. Melton
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 17, Iss S2, Pp 15-22 (2017)
Abstract Background Automated methods for identifying clinically relevant new versus redundant information in electronic health record (EHR) clinical notes is useful for clinicians and researchers involved in patient care and clinical research, respe
Externí odkaz:
https://doaj.org/article/5572d86515bc4cd5a448071ee826bfc8
Autor:
Jon C. Schommer, Lawrence M. Brown, Ryan (Alyssa) Bortz, Alina Cernasev, Basma T. Gomaa, Keri D. Hager, Lisa Hillman, Olihe Okoro, Serguei V. S. Pakhomov, Paul L. Ranelli
Publikováno v:
Pharmacy, Vol 6, Iss 3, p 78 (2018)
Pharmacist workforce researchers are predicting a potential surplus of pharmacists in the United States that might result in pharmacists being available for engagement in new roles. The objective for this study was to describe consumer opinions regar
Externí odkaz:
https://doaj.org/article/774d508a831b4d7993077702aa5b511e
Autor:
Raymond L. Finzel, Michael A. Puskarich, John Sartori, James Dries, Greg M. Silverman, Rui Zhang, Monica I. Lupei, György J. Simon, Christopher J. Tignanelli, Serguei V. S. Pakhomov, Himanshu S. Sahoo, Genevieve B. Melton, Nicholas E. Ingraham, Michael G. Usher, Eric Murray
Publikováno v:
Journal of Artificial Intelligence Research. 72:429-474
Statistical modeling of outcomes based on a patient's presenting symptoms (symptomatology) can help deliver high quality care and allocate essential resources, which is especially important during the COVID-19 pandemic. Patient symptoms are typically
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f2175bf64cb24b5cd6c064094e318ea
https://doi.org/10.1613/jair.1.12631
https://doi.org/10.1613/jair.1.12631
Autor:
Hongfang Liu, Jianfu Li, Serguei V. S. Pakhomov, Xiaoqian Jiang, Yujia Zhou, Hua Xu, Karthik Natarajan
Publikováno v:
J Am Med Inform Assoc
Objective : Developing clinical natural language processing systems often requires access to many clinical documents, which are not widely available to the public due to privacy and security concerns. To address this challenge, we propose to develop
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::452585b664caf1853862aa8c88d65424
https://doi.org/10.1093/jamia/ocab112
https://doi.org/10.1093/jamia/ocab112
Autor:
Hongfang Liu, Sijia Liu, Nicholas E. Ingraham, Serguei V. S. Pakhomov, Himanshu S. Sahoo, Christopher J. Tignanelli, Rui Zhang, Genevieve B. Melton, Monica I. Lupei, John Sartori, Benjamin C. Knoll, Michael A. Puskarich, Raymond L. Finzel, Greg M. Silverman
Publikováno v:
JAMIA Open
Objective With COVID-19, there was a need for a rapidly scalable annotation system that facilitated real-time integration with clinical decision support systems (CDS). Current annotation systems suffer from a high-resource utilization and poor scalab
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ce77adf94890506a48af9f174a538090
http://europepmc.org/articles/PMC8374371
http://europepmc.org/articles/PMC8374371
Publikováno v:
Frontiers in Computer Science, Vol 3 (2021)
Large amounts of labeled data are a prerequisite to training accurate and reliable machine learning models. However, in the medical domain in particular, this is also a stumbling block as accurately labeled data are hard to obtain. DementiaBank, a pu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::89010ebc801d5601e4e7fde82ac9aae6
https://doi.org/10.3389/fcomp.2021.642517
https://doi.org/10.3389/fcomp.2021.642517
Publikováno v:
EACL (System Demonstrations)
Experts@Minnesota
Experts@Minnesota
Conversational Agent for Daily Living Assessment Coaching (CADLAC) is a multi-modal conversational agent system designed to impersonate “individuals” with various levels of ability in activities of daily living (ADLs: e.g., dressing, bathing, mob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0757e24f3a6d79202c8fd1a68a1f77ed
https://doi.org/10.18653/v1/2021.eacl-demos.38
https://doi.org/10.18653/v1/2021.eacl-demos.38
Autor:
Michael Lucke, Libby Ferland, Serguei V. S. Pakhomov, Maria Gini, Jude Sauve, Malik Khadar, Runpeng Nie
Publikováno v:
Explainable AI in Healthcare and Medicine ISBN: 9783030533519
Growing interest in applications of AI in healthcare has led to a similarly elevated interest in fully integrated smart systems in which disparate technologies, such as biometric sensors and conversational agents, are combined to address health probl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aa8524e1bcf3f65d6d2438be5f8ea8b3
https://doi.org/10.1007/978-3-030-53352-6_28
https://doi.org/10.1007/978-3-030-53352-6_28
Autor:
Anusha Bompelli, Andrew Yang, Serguei V. S. Pakhomov, Esha Singh, Rui Zhang, Andrew Shengli Wang
Publikováno v:
ICHI
According to National Institute of Standards and Technology (DSQAP), approximately 8 out of every 10 people in the United States take dietary supplements, including vitamins and mineral supplements, representing an annual expenditure of more than $40
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2da1d6996333ae49b2b58a04a834fa01
https://doi.org/10.1109/ichi48887.2020.9374355
https://doi.org/10.1109/ichi48887.2020.9374355
Autor:
Amy M. Sitapati, Serguei V. S. Pakhomov, Hongfang Liu, Swapna Abhyankar, Jianfu Li, Theresa Cullen, Robert Murphy, Elizabeth Hanchrow, Hua Xu, Xiaoqian Jiang, Ruth M. Reeves, Jian-Guo Bian, Lucila Ohno-Machado, Michael E. Matheny, Scott L. DuVall, Karthik Natarajan, Kristine E. Lynch, Xiao Dong, Ekin Soysal, Jami Deckard
Publikováno v:
Journal of the American Medical Informatics Association : JAMIA
Journal of the American Medical Informatics Association
Journal of the American Medical Informatics Association
Large observational data networks that leverage routine clinical practice data in electronic health records (EHRs) are critical resources for research on coronavirus disease 2019 (COVID-19). Data normalization is a key challenge for the secondary use
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b98b9d537df02a75cbf3322c0149ec63
http://europepmc.org/articles/PMC7337837
http://europepmc.org/articles/PMC7337837