Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Qianzi, Li"'
Autor:
Samuel Joseph Kaplan, Wilfred Wong, Jielin Yan, Julian Pulecio, Hyein S. Cho, Qianzi Li, Jiahui Zhao, Jayanti Leslie-Iyer, Jonathan Kazakov, Dylan Murphy, Renhe Luo, Kushal K. Dey, Effie Apostolou, Christina S. Leslie, Danwei Huangfu
Publikováno v:
Cell Reports, Vol 43, Iss 8, Pp 114640- (2024)
Summary: Functional enhancer annotation is critical for understanding tissue-specific transcriptional regulation and prioritizing disease-associated non-coding variants. However, unbiased enhancer discovery in disease-relevant contexts remains challe
Externí odkaz:
https://doaj.org/article/18884ea54402465ca393dbb1bcd2118f
Autor:
Josue, Barnes, Matthew, Brendel, Vianne R, Gao, Suraj, Rajendran, Junbum, Kim, Qianzi, Li, Jonas E, Malmsten, Jose T, Sierra, Pantelis, Zisimopoulos, Alexandros, Sigaras, Pegah, Khosravi, Marcos, Meseguer, Qiansheng, Zhan, Zev, Rosenwaks, Olivier, Elemento, Nikica, Zaninovic, Iman, Hajirasouliha
Publikováno v:
The Lancet Digital Health. 5:e28-e40
One challenge in the field of in-vitro fertilisation is the selection of the most viable embryos for transfer. Morphological quality assessment and morphokinetic analysis both have the disadvantage of intra-observer and inter-observer variability. A
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::091dcbec9cd745258a12b822ab39214e
https://doi.org/10.1016/s2589-7500(22)00213-8
https://doi.org/10.1016/s2589-7500(22)00213-8
Autor:
Maria Lysandrou, Bilal Chughtai, Brian D. Robinson, Iman Hajirasouliha, Josue Barnes, Matthew Brendel, Olivier Elemento, Alexandros Sigaras, Andy Yat, Ehsan Kazemi, Pegah Khosravi, Andrea Sboner, Pantelis Zisimopoulos, Timothy D. McClure, Mahmoud Eljalby, Camir Ricketts, Qianzi Li, Dmitry Meleshko
Publikováno v:
Journal of Magnetic Resonance Imaging
Background A definitive diagnosis of prostate cancer requires a biopsy to obtain tissue for pathologic analysis, but this is an invasive procedure and is associated with complications. Purpose To develop an artificial intelligence (AI)-based model (n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8f61afe2cff2b726dd1627aec280e3e6
http://europepmc.org/articles/PMC8360022
http://europepmc.org/articles/PMC8360022
Autor:
Pantelis Zisimopoulos, Timothy D. McClure, Mahmoud Eljalby, Ehsan Kazemi, Camir Ricketts, Andrea Sboner, Josue Barnes, Iman Hajirasouliha, Qianzi Li, Bilal Chughtai, Olivier Elemento, Dimitri Meleshko, Matthew Brendel, Maria Lysandrou, Alexandros Sigaras, Brian D. Robinson, Andy Yat, Pegah Khosravi
Magnetic Resonance Imaging (MRI) is routinely used to visualize the prostate gland and manage prostate cancer. The Prostate Imaging Reporting And Data System (PI-RADS) is used to evaluate the clinical risk associated with a potential tumor. However t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0a539ec507ada19f4d259ed9837c0687
https://doi.org/10.1101/2019.12.16.19015057
https://doi.org/10.1101/2019.12.16.19015057
