Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Yuanshan Wu"'
Autor:
Marco Toto-Brocchi, Yuanshan Wu, Saeed Jerban, Aiguo Han, Michael Andre, Sameer B. Shah, Eric Y. Chang
Publikováno v:
European Radiology Experimental, Vol 8, Iss 1, Pp 1-9 (2024)
Abstract Background To prospectively evaluate ultrasound backscatter coefficients (BSCs) of the supraspinatus and infraspinatus muscles and compare with Goutallier classification on magnetic resonance imaging (MRI). Methods Fifty-six participants had
Externí odkaz:
https://doaj.org/article/128aa27be6884ce39739a9dde81af06f
Autor:
Saeed Jerban, Victor Barrere, Behnam Namiranian, Yuanshan Wu, Salem Alenezi, Erik Dorthe, Darryl Dlima, Sameer B. Shah, Christine B. Chung, Jiang Du, Michael P. Andre, Eric Y. Chang
Publikováno v:
European Radiology Experimental, Vol 8, Iss 1, Pp 1-13 (2024)
Abstract Background We investigated the relationship of two commonly used quantitative ultrasound (QUS) parameters, speed of sound (SoS) and attenuation coefficient (α), with water and macromolecular contents of bovine cortical bone strips as measur
Externí odkaz:
https://doaj.org/article/387b6651eedb413bbccb30a64e0dee30
Autor:
Yuanshan Wu, Victor Barrere, Aiguo Han, Michael P. Andre, Elisabeth Orozco, Xin Cheng, Eric Y. Chang, Sameer B. Shah
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-17 (2023)
Abstract In this study, we evaluated the utility of using high-frequency ultrasound to non-invasively track the degenerative process in a rat model of peripheral nerve injury. Primary analyses explored spatial and temporal changes in quantitative bac
Externí odkaz:
https://doaj.org/article/4c3be86a455d46c28512ec82eeb5f0d1
Autor:
Qingbo Tang, Yajun Ma, Qun Cheng, Yuanshan Wu, Junyuan Chen, Jiang Du, Pengzhe Lu, Eric Y. Chang
Publikováno v:
Journal of Imaging, Vol 10, Iss 9, p 213 (2024)
Quantitative MRI techniques could be helpful to noninvasively and longitudinally monitor dynamic changes in spinal cord white matter following injury, but imaging and postprocessing techniques in small animals remain lacking. Unilateral C5 hemisectio
Externí odkaz:
https://doaj.org/article/e2179f33913b4591a034c8b36476ca73
Publikováno v:
Electronic Research Archive, Vol 30, Iss 5, Pp 1936-1953 (2022)
The emergence of massive data has driven recent interest in developing statistical learning and large-scale algorithms for analysis on distributed platforms. One of the widely used statistical approaches is split-and-conquer (SaC), which was original
Externí odkaz:
https://doaj.org/article/b0eb78c8813f4ed783025e1b6fb9a4db
Autor:
Aria Ashir, Saeed Jerban, Victor Barrère, Yuanshan Wu, Sameer B. Shah, Michael P. Andre, Eric Y. Chang
Publikováno v:
Sensors, Vol 23, Iss 10, p 4763 (2023)
Ultrasound (US) is an important imaging tool for skeletal muscle analysis. The advantages of US include point-of-care access, real-time imaging, cost-effectiveness, and absence of ionizing radiation. However, US can be highly dependent on the operato
Externí odkaz:
https://doaj.org/article/71bfc0c026924c699ebebb26d340a22d
Publikováno v:
International Journal of Distributed Sensor Networks, Vol 12 (2016)
Although traditional spatial-temporal features, such as gyration, probability, and the intervals between consecutive records, have contributed to model human dynamics, the importance of these basic spatial-temporal features in predicting mobile user
Externí odkaz:
https://doaj.org/article/71e656fe5a9d48fe8ac9aea8323bb8cf
Publikováno v:
Statistics in Medicine. 42:860-877
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e98ad20cfb58180ec4c997509145c7d
https://doi.org/10.1002/sim.9647
https://doi.org/10.1002/sim.9647
Publikováno v:
Ultrasound in Medicine & Biology. 49:122-135
Ultrasound (US) is an increasingly prevalent and effective diagnostic modality for neuromuscular imaging. Gray-scale B-mode imaging has been the dominant US approach to evaluating nerves qualitatively or making morphometric measurements of nerves, pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bec50e176a711eb17927b783d4363c85
https://doi.org/10.1016/j.ultrasmedbio.2022.08.007
https://doi.org/10.1016/j.ultrasmedbio.2022.08.007
Publikováno v:
Lifetime Data Analysis. 29:115-141
We propose an inferential procedure for additive hazards regression with high-dimensional survival data, where the covariates are prone to measurement errors. We develop a double bias correction method by first correcting the bias arising from measur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a111c8ae5958211e90900548d52e6a6
https://doi.org/10.1007/s10985-022-09568-2
https://doi.org/10.1007/s10985-022-09568-2