Zobrazeno 1 - 10
of 2 165
pro vyhledávání: '"Stewart, Paul A."'
Cancer clinics capture disease data at various scales, from genetic to organ level. Current bioinformatic methods struggle to handle the heterogeneous nature of this data, especially with missing modalities. We propose PARADIGM, a Graph Neural Networ
Externí odkaz:
http://arxiv.org/abs/2406.08521
Autor:
Waqas, Asim, Tripathi, Aakash, Ahmed, Sabeen, Mukund, Ashwin, Farooq, Hamza, Schabath, Matthew B., Stewart, Paul, Naeini, Mia, Rasool, Ghulam
Multi-omics research has enhanced our understanding of cancer heterogeneity and progression. Investigating molecular data through multi-omics approaches is crucial for unraveling the complex biological mechanisms underlying cancer, thereby enabling e
Externí odkaz:
http://arxiv.org/abs/2405.08226
Autor:
Connolly, Heather, Stewart, Paul
Publikováno v:
Work Organisation, Labour & Globalisation, 2024 Apr 01. 18(1), 83-96.
Externí odkaz:
https://www.jstor.org/stable/48774387
Cancer has relational information residing at varying scales, modalities, and resolutions of the acquired data, such as radiology, pathology, genomics, proteomics, and clinical records. Integrating diverse data types can improve the accuracy and reli
Externí odkaz:
http://arxiv.org/abs/2303.06471
Autor:
Karolak, Aleksandra, Urbaniak, Konstancja, Monastyrskyi, Andrii, Duckett, Derek R., Branciamore, Sergio, Stewart, Paul A.
Publikováno v:
In Biophysical Journal 3 September 2024 123(17):2910-2920
Autor:
Alontaga, Aileen Y., Cano, Pedro, Ozakinci, Hilal, Puskas, John A., Stewart, Paul A., Welsh, Eric A., Yoder, Sean J., Hicks, J. Kevin, Saltos, Andreas N., Bossler, Aaron D., Haura, Eric B., Koomen, John M., Boyle, Theresa A.
Publikováno v:
In The Journal of Molecular Diagnostics August 2024 26(8):685-699
Autor:
Peak, Taylor, Tian, Yijun, Patel, Aman, Shaw, Tim, Obermayer, Alyssa, Laborde, Jose, Kim, Youngchul, Johnson, Joseph, Stewart, Paul, Fang, Bin, Teer, Jamie K., Koomen, John, Berglund, Anders, Marchion, Doug, Francis, Natasha, Echevarria, Paola Ramos, Dhillon, Jasreman, Clark, Noel, Chang, Andrew, Sexton, Wade, Zemp, Logan, Chahoud, Jad, Wang, Liang, Manley, Brandon
Publikováno v:
In Laboratory Investigation May 2024 104(5)
Autor:
Lee, Benjamin D., Gitter, Anthony, Greene, Casey S., Raschka, Sebastian, Maguire, Finlay, Titus, Alexander J., Kessler, Michael D., Lee, Alexandra J., Chevrette, Marc G., Stewart, Paul Allen, Britto-Borges, Thiago, Cofer, Evan M., Yu, Kun-Hsing, Carmona, Juan Jose, Fertig, Elana J., Kalinin, Alexandr A., Signal, Beth, Lengerich, Benjamin J., Triche Jr, Timothy J., Boca, Simina M.
Machine learning is a modern approach to problem-solving and task automation. In particular, machine learning is concerned with the development and applications of algorithms that can recognize patterns in data and use them for predictive modeling. A
Externí odkaz:
http://arxiv.org/abs/2105.14372
Autor:
Adhikari, Emma, Liu, Qian, Johnson, Joseph, Stewart, Paul, Marusyk, Viktoriya, Fang, Bin, Izumi, Victoria, Bowers, Kiah, Guzman, Kelly M., Koomen, John M., Marusyk, Andriy, Lau, Eric K.
Publikováno v:
In Cell Reports 26 December 2023 42(12)
Akademický článek
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