Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Kitty Yu-Yeung Lau"'
Autor:
Jie Lian, Fan Huang, Xinhai Huang, Kitty Yu-Yeung Lau, Kei Shing Ng, Carlin Chun Fai Chu, Simon Ching Lam, Mohamad Koohli-Moghadam, Varut Vardhanabhuti
Publikováno v:
BMC Infectious Diseases, Vol 24, Iss 1, Pp 1-11 (2024)
Abstract Background Predicting an individual’s risk of death from COVID-19 is essential for planning and optimising resources. However, since the real-world mortality rate is relatively low, particularly in places like Hong Kong, this makes buildin
Externí odkaz:
https://doaj.org/article/20984507519c41459606b435c1104f6f
Autor:
Kitty Yu-Yeung Lau, Kei-Shing Ng, Ka-Wai Kwok, Kevin Kin-Man Tsia, Chun-Fung Sin, Ching-Wan Lam, Varut Vardhanabhuti
Publikováno v:
Frontiers in Medicine, Vol 8 (2022)
BackgroundTo better understand the different clinical phenotypes across the disease spectrum in patients with COVID-19 using an unsupervised machine learning clustering approach.Materials and MethodsA population-based retrospective study was conducte
Externí odkaz:
https://doaj.org/article/29085441883d4dea818d456b84f346b0
BACKGROUND Novel coronaviruses have emerged and caused major epidemics and pandemics in the past two decades, including severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1), Middle East respiratory syndrome coronavirus (MERS-CoV), and severe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::206bdaea9ed48549161ef750d8c1d6ae
https://doi.org/10.2196/preprints.46687
https://doi.org/10.2196/preprints.46687
Autor:
Kitty Yu-Yeung Lau, Kei-Shing Ng, Ka-Wai Kwok, Kevin Kin-Man Tsia, Chun-Fung Sin, Ching-Wan Lam, Varut Vardhanabhuti
Publikováno v:
Frontiers in medicine. 8
BackgroundTo better understand the different clinical phenotypes across the disease spectrum in patients with COVID-19 using an unsupervised machine learning clustering approach.Materials and MethodsA population-based retrospective study was conducte
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e26e4d6a1d50a1e153718f656f82050e
https://pubmed.ncbi.nlm.nih.gov/35284429
https://pubmed.ncbi.nlm.nih.gov/35284429
Publikováno v:
Advanced Biosystems. 3:1900076
Single-cell analysis has shown great potential to fully quantify the distribution of cellular behaviors among a population of individuals. Through isolation and preservation of single cells in the aqueous phase, droplet encapsulation followed by gela
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d100134687fe506b280ce2d9d1b88f4
https://doi.org/10.1002/adbi.201900076
https://doi.org/10.1002/adbi.201900076