Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Namu Park"'
Autor:
Se Min Kim, Namu Park, Hye Bin Park, JuKyung Lee, Changho Chun, Kyung Hoon Kim, Jong Seob Choi, Hyung Jin Kim, Sekyu Choi, Jung Hyun Lee
Publikováno v:
PLoS ONE, Vol 19, Iss 5, p e0303433 (2024)
Triple-negative breast cancer (TNBC) demands urgent attention for the development of effective treatment strategies due to its aggressiveness and limited therapeutic options [1]. This research is primarily focused on identifying new biomarkers vital
Externí odkaz:
https://doaj.org/article/06b8dfaed683424abfb551d109085d21
Autor:
Hyung Jun Park, Namu Park, Jang Ho Lee, Myeong Geun Choi, Jin-Sook Ryu, Min Song, Chang-Min Choi
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 22, Iss 1, Pp 1-11 (2022)
Abstract Background Extracting metastatic information from previous radiologic-text reports is important, however, laborious annotations have limited the usability of these texts. We developed a deep-learning model for extracting primary lung cancer
Externí odkaz:
https://doaj.org/article/13f3888b5f90479d854212839b16f806
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-9 (2022)
Abstract Blood and fluid analysis is extensively used for classifying the etiology of pleural effusion. However, most studies focused on determining the presence of a disease. This study classified pleural effusion etiology employing deep learning mo
Externí odkaz:
https://doaj.org/article/ce8cfc83c9f54cd9b72dbd4543b00191
Autor:
Qi Yu, Qi Wang, Yafei Zhang, Chongyan Chen, Hyeyoung Ryu, Namu Park, Jae-Eun Baek, Keyuan Li, Yifei Wu, Daifeng Li, Jian Xu, Meijun Liu, Jeremy J. Yang, Chenwei Zhang, Chao Lu, Peng Zhang, Xin Li, Baitong Chen, Islam Akef Ebeid, Julia Fensel, Chao Min, Yujia Zhai, Min Song, Ying Ding, Yi Bu
Publikováno v:
Scientometrics. 127:2127-2129
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0ca512819eea130c4e09c774599fd66d
https://doi.org/10.1007/s11192-022-04311-y
https://doi.org/10.1007/s11192-022-04311-y
Publikováno v:
Scientific reports. 12(1)
Blood and fluid analysis is extensively used for classifying the etiology of pleural effusion. However, most studies focused on determining the presence of a disease. This study classified pleural effusion etiology employing deep learning models by a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60ca03b579827e9bdc9bfc1a93545bea
https://pubmed.ncbi.nlm.nih.gov/35365722
https://pubmed.ncbi.nlm.nih.gov/35365722
Autor:
Chenwei Zhang, Min Song, Baitong Chen, Chongyan Chen, Yujia Zhai, Qi Wang, Jae Eun Baek, Ying Ding, Yi Bu, Chao Min, Peng Zhang, Meijun Liu, Qi Yu, Xin Li, Namu Park, Yifei Wu, Chao Lu, Julia Fensel, Jian Xu, Daifeng Li, Jeremy J. Yang, Yafei Zhang, Islam Akef Ebeid, Keyuan Li, Hyeyoung Ryu
Publikováno v:
Scientometrics
COVID-19 cases have surpassed the 109 + million markers, with deaths tallying up to 2.4 million. Tens of thousands of papers regarding COVID-19 have been published along with countless bibliometric analyses done on COVID-19 literature. Despite this,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b7ce441f50477d3f792d263e565fedaa
https://pubmed.ncbi.nlm.nih.gov/33746309
https://pubmed.ncbi.nlm.nih.gov/33746309
Drug repurposing may be a pivotal means of fulfilling urgent needs for treatment of the novel coronavirus disease 2019 (COVID-19), but current studies on drug repurposing for COVID-19 seem to show a lack of consensus in their drug candidate focus. Us
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6567e9b09c44f4cf099185149d471bcb
https://doi.org/10.21203/rs.3.rs-80893/v1
https://doi.org/10.21203/rs.3.rs-80893/v1
