Zobrazeno 1 - 10
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pro vyhledávání: '"Stevens, P M"'
Autor:
Gu, Hongyan, Yang, Chunxu, Magaki, Shino, Zarrin-Khameh, Neda, Lakis, Nelli S., Cobos, Inma, Khanlou, Negar, Zhang, Xinhai R., Assi, Jasmeet, Byers, Joshua T., Hamza, Ameer, Han, Karam, Meyer, Anders, Mirbaha, Hilda, Mohila, Carrie A., Stevens, Todd M., Stone, Sara L., Yan, Wenzhong, Haeri, Mohammad, Chen, Xiang 'Anthony'
As Artificial Intelligence (AI) making advancements in medical decision-making, there is a growing need to ensure doctors develop appropriate reliance on AI to avoid adverse outcomes. However, existing methods in enabling appropriate AI reliance migh
Externí odkaz:
http://arxiv.org/abs/2404.04485
Autor:
Georgiev, Dimitar, Fernández-Galiana, Álvaro, Pedersen, Simon Vilms, Papadopoulos, Georgios, Xie, Ruoxiao, Stevens, Molly M., Barahona, Mauricio
Publikováno v:
Proceedings of the National Academy of Sciences, 2024, 121(44), e2321305121
Raman spectroscopy is widely used across scientific domains to characterize the chemical composition of samples in a non-destructive, label-free manner. Many applications entail the unmixing of signals from mixtures of molecular species to identify t
Externí odkaz:
http://arxiv.org/abs/2403.04526
With the rise in engineered biomolecular devices, there is an increased need for tailor-made biological sequences. Often, many similar biological sequences need to be made for a specific application meaning numerous, sometimes prohibitively expensive
Externí odkaz:
http://arxiv.org/abs/2402.17704
Autor:
Georgiev, Dimitar, Pedersen, Simon Vilms, Xie, Ruoxiao, Fernández-Galiana, Álvaro, Stevens, Molly M., Barahona, Mauricio
Publikováno v:
Anal. Chem. 2024, 96, 21, 8492-8500
Raman spectroscopy is a non-destructive and label-free chemical analysis technique, which plays a key role in the analysis and discovery cycle of various branches of science. Nonetheless, progress in Raman spectroscopic analysis is still impeded by t
Externí odkaz:
http://arxiv.org/abs/2307.13650
Autor:
Pedersen, Simon Vilms, Walther, Anders R., Callanan, Anthony, Stevens, Molly M., Hedegaard, Martin A. B., Arnspang, Eva C.
Unsupervised estimation of the dimensionality of hyperspectral microspectroscopy datasets containing pure and mixed spectral features, and extraction of their representative endmember spectra, remains a challenge in biochemical data mining. We report
Externí odkaz:
http://arxiv.org/abs/2210.03238
Autor:
Horgan, Conor C., Jensen, Magnus, Nagelkerke, Anika, St-Pierre, Jean-Phillipe, Vercauteren, Tom, Stevens, Molly M., Bergholt, Mads S.
Raman spectroscopy enables non-destructive, label-free imaging with unprecedented molecular contrast but is limited by slow data acquisition, largely preventing high-throughput imaging applications. Here, we present a comprehensive framework for high
Externí odkaz:
http://arxiv.org/abs/2009.13318
Autor:
Horgan, Conor C., Bergholt, Mads S., Thin, May Zaw, Nagelkerke, Anika, Kennedy, Robert, Kalber, Tammy L., Stuckey, Daniel J., Stevens, Molly M.
The initial detection and identification of suspicious lesions and the precise delineation of tumour mar-gins are essential for successful tumour resection, with progression-free survival linked to rates of complete resection. However, post-surgical
Externí odkaz:
http://arxiv.org/abs/2009.11652
Autor:
Horgan, Conor C., Bergholt, Mads S., Nagelkerke, Anika, Thin, May Zaw, Pence, Isaac J., Kauscher, Ulrike, Kalber, Tammy L., Stuckey, Daniel J., Stevens, Molly M.
Theranostics, the combination of diagnosis and therapy, has long held promise as a means to achieving personalised precision cancer treatments. However, despite its potential, theranostics has yet to realise significant clinical translation, largely
Externí odkaz:
http://arxiv.org/abs/2009.04222
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Akademický článek
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