Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Thienkhai Vu"'
Autor:
Yeshwant Reddy Chillakuru, Shourya Munjal, Benjamin Laguna, Timothy L. Chen, Gunvant R. Chaudhari, Thienkhai Vu, Youngho Seo, Jared Narvid, Jae Ho Sohn
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 21, Iss 1, Pp 1-10 (2021)
Abstract Background A systematic approach to MRI protocol assignment is essential for the efficient delivery of safe patient care. Advances in natural language processing (NLP) allow for the development of accurate automated protocol assignment. We a
Externí odkaz:
https://doaj.org/article/f0657fccdd3747b78beddbed5ad57d3a
Autor:
Yeshwant Reddy Chillakuru, Kyle Kranen, Vishnu Doppalapudi, Zhangyuan Xiong, Letian Fu, Aarash Heydari, Aditya Sheth, Youngho Seo, Thienkhai Vu, Jae Ho Sohn
Publikováno v:
BMC Medical Imaging, Vol 21, Iss 1, Pp 1-13 (2021)
Abstract Background Reidentification of prior nodules for temporal comparison is an important but time-consuming step in lung cancer screening. We develop and evaluate an automated nodule detector that utilizes the axial-slice number of nodules found
Externí odkaz:
https://doaj.org/article/295733fd02b340408385405df3b90de7
Autor:
Benjamin Laguna, Youngho Seo, Thienkhai Vu, Shourya Munjal, Jae Ho Sohn, Gunvant R. Chaudhari, Jared Narvid, Timothy L. Chen, Yeshwant Chillakuru
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 21, Iss 1, Pp 1-10 (2021)
BMC medical informatics and decision making, vol 21, iss 1
BMC Medical Informatics and Decision Making
BMC medical informatics and decision making, vol 21, iss 1
BMC Medical Informatics and Decision Making
Background A systematic approach to MRI protocol assignment is essential for the efficient delivery of safe patient care. Advances in natural language processing (NLP) allow for the development of accurate automated protocol assignment. We aim to dev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3915dc98895265eb6c0b69b9f396c1a4
https://doaj.org/article/f0657fccdd3747b78beddbed5ad57d3a
https://doaj.org/article/f0657fccdd3747b78beddbed5ad57d3a
Autor:
Benjamin L. Franc, Thienkhai Vu, Jaewon Yang, Yixin Chen, Jae Ho Sohn, Dexter Hadley, Youngho Seo, Dmytro Lituiev, Karen G. Ordovas
Publikováno v:
Scientific reports, vol 12, iss 1
Our objective was to develop deep learning models with chest radiograph data to predict healthcare costs and classify top-50% spenders. 21,872 frontal chest radiographs were retrospectively collected from 19,524 patients with at least 1-year spending
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b4f1ce881060425f95fbdbaa5c69001d
https://escholarship.org/uc/item/3863t1vt
https://escholarship.org/uc/item/3863t1vt
Autor:
Jae Ho Sohn, Aditya Sheth, Vishnu Doppalapudi, Thienkhai Vu, Kyle Kranen, Youngho Seo, Zhangyuan Xiong, Aarash Heydari, Letian Fu, Yeshwant Chillakuru
Publikováno v:
BMC Medical Imaging
BMC Medical Imaging, Vol 21, Iss 1, Pp 1-13 (2021)
BMC medical imaging, vol 21, iss 1
BMC Medical Imaging, Vol 21, Iss 1, Pp 1-13 (2021)
BMC medical imaging, vol 21, iss 1
BackgroundReidentification of prior nodules for temporal comparison is an important but time-consuming step in lung cancer screening. We develop and evaluate an automated nodule detector that utilizes the axial-slice number of nodules found in radiol
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1b7e0899a96db95ba0a2dadc10f66ecf
http://europepmc.org/articles/PMC8034095
http://europepmc.org/articles/PMC8034095
Publikováno v:
Academic radiology. 29(5)
Rationale and Objectives Radiology turnaround time is an important quality measure that can impact hospital workflow and patient outcomes. We aimed to develop a machine learning model to predict delayed turnaround time during non-business hours and i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d6d4f3980682dadbba06e58bab40bcde
https://pubmed.ncbi.nlm.nih.gov/34187741
https://pubmed.ncbi.nlm.nih.gov/34187741
Autor:
Yeshwant Chillakuru, Thienkhai Vu, Bonnie N. Joe, Amie Y. Lee, Stanley Lee, Youngho Seo, Tatiana Kelil, Jae Ho Sohn, Christopher P. Hess
Publikováno v:
J Digit Imaging
Although machine learning (ML) has made significant improvements in radiology, few algorithms have been integrated into clinical radiology workflow. Complex radiology IT environments and Picture Archiving and Communication System (PACS) pose unique c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9bc48d479d48d0a50f8454919ac43c60
https://pubmed.ncbi.nlm.nih.gov/32468486
https://pubmed.ncbi.nlm.nih.gov/32468486
Autor:
Gunvant R. Chaudhari, Max Emerling, Youngho Seo, Yeshwant Chillakuru, Thienkhai Vu, Jae Ho Sohn, Timothy L. Chen
Publikováno v:
J Biomed Inform
BACKGROUND: There has been increasing interest in machine learning based natural language processing (NLP) methods in radiology; however, models have often used word embeddings trained on general web corpora due to lack of a radiology-specific corpus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94c77515d8185f8c74e9c8a18f95fca9
https://doi.org/10.1016/j.jbi.2020.103665
https://doi.org/10.1016/j.jbi.2020.103665
Autor:
Chillakuru, Yeshwant Reddy, Munjal, Shourya, Laguna, Benjamin, Chen, Timothy L., Chaudhari, Gunvant R., Thienkhai Vu, Youngho Seo, Narvid, Jared, Jae Ho Sohn, Vu, Thienkhai, Seo, Youngho, Sohn, Jae Ho
Publikováno v:
BMC Medical Informatics & Decision Making; 7/12/2021, Vol. 21 Issue 1, p1-10, 10p, 2 Diagrams, 3 Charts, 2 Graphs
Publikováno v:
Journal of digital imaging, vol 31, iss 2
Magnetic resonance imaging (MRI) protocoling can be time- and resource-intensive, and protocols can often be suboptimal dependent upon the expertise or preferences of the protocoling radiologist. Providing a best-practice recommendation for an MRI pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39eec7e4d48637b2174bc4174868b87c
https://pubmed.ncbi.nlm.nih.gov/28924815
https://pubmed.ncbi.nlm.nih.gov/28924815