Zobrazeno 1 - 10
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pro vyhledávání: '"Waqas, Asim"'
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
Developing accurate machine learning models for oncology requires large-scale, high-quality multimodal datasets. However, creating such datasets remains challenging due to the complexity and heterogeneity of medical data. To address this challenge, w
Externí odkaz:
http://arxiv.org/abs/2405.07460
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
The advancements in data acquisition, storage, and processing techniques have resulted in the rapid growth of heterogeneous medical data. Integrating radiological scans, histopathology images, and molecular information with clinical data is essential
Externí odkaz:
http://arxiv.org/abs/2310.01438
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
Publikováno v:
Commun Eng 1, 46 (2022)
The architectures of deep artificial neural networks (DANNs) are routinely studied to improve their predictive performance. However, the relationship between the architecture of a DANN and its robustness to noise and adversarial attacks is less explo
Externí odkaz:
http://arxiv.org/abs/2106.15850
Autor:
Tripathi, Aakash1,2 (AUTHOR) aakash.tripathi@moffitt.org, Waqas, Asim1,2 (AUTHOR) kavya.venkatesan@moffitt.org, Venkatesan, Kavya1 (AUTHOR) ghulam.rasool@moffitt.org, Yilmaz, Yasin2 (AUTHOR), Rasool, Ghulam1,2,3,4 (AUTHOR)
Publikováno v:
Sensors (14248220). Mar2024, Vol. 24 Issue 5, p1634. 29p.
Autor:
Waqas, Asim, Bui, Marilyn M., Glassy, Eric F., El Naqa, Issam, Borkowski, Piotr, Borkowski, Andrew A., Rasool, Ghulam
Publikováno v:
In Laboratory Investigation November 2023 103(11)
Publikováno v:
Frontiers in Artificial Intelligence; 2024, p1-24, 24p
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