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pro vyhledávání: '"Siegel, Eliot"'
Large-scale medical imaging datasets have accelerated development of artificial intelligence tools for clinical decision support. However, the large size of these datasets is a bottleneck for users with limited storage and bandwidth. Many users may n
Externí odkaz:
http://arxiv.org/abs/2307.00438
As the adoption of Artificial Intelligence (AI) systems within the clinical environment grows, limitations in bandwidth and compute can create communication bottlenecks when streaming imaging data, leading to delays in patient care and increased cost
Externí odkaz:
http://arxiv.org/abs/2305.15617
Autor:
Rahmim, Arman, Bradshaw, Tyler J., Buvat, Irène, Dutta, Joyita, Jha, Abhinav K., Kinahan, Paul E., Li, Quanzheng, Liu, Chi, McCradden, Melissa D., Saboury, Babak, Siegel, Eliot, Sunderland, John J., Wahl, Richard L.
The SNMMI Artificial Intelligence (SNMMI-AI) Summit, organized by the SNMMI AI Task Force, took place in Bethesda, MD on March 21-22, 2022. It brought together various community members and stakeholders from academia, healthcare, industry, patient re
Externí odkaz:
http://arxiv.org/abs/2211.03783
Publikováno v:
PET clinics 16, no. 4 (2021): 449-469
The field of artificial intelligence (AI), regarded as one of the most enigmatic areas of science, has witnessed exponential growth in the past decade including a remarkably wide array of applications, having already impacted our everyday lives. Adva
Externí odkaz:
http://arxiv.org/abs/2109.01517
Autor:
Doo, Florence X., Kulkarni, Pranav, Siegel, Eliot L., Toland, Michael, Yi, Paul H., Carlos, Ruth C., Parekh, Vishwa S.
Publikováno v:
In Journal of the American College of Radiology February 2024 21(2):248-256
Autor:
Gozes, Ophir, Frid-Adar, Maayan, Greenspan, Hayit, Browning, Patrick D., Zhang, Huangqi, Ji, Wenbin, Bernheim, Adam, Siegel, Eliot
Purpose: Develop AI-based automated CT image analysis tools for detection, quantification, and tracking of Coronavirus; demonstrate they can differentiate coronavirus patients from non-patients. Materials and Methods: Multiple international datasets,
Externí odkaz:
http://arxiv.org/abs/2003.05037
Akademický článek
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Autor:
Doo, Florence X., Cook, Tessa S., Siegel, Eliot L., Joshi, Anupam, Parekh, Vishwa, Elahi, Ameena, Yi, Paul H.
Publikováno v:
In Journal of the American College of Radiology September 2023 20(9):877-885
Publikováno v:
In Academic Radiology May 2023 30(5):971-974
Autor:
Adams, Scott J., Madtes, David K., Burbridge, Brent, Johnston, Josiah, Goldberg, Ilya G., Siegel, Eliot L., Babyn, Paul, Nair, Viswam S., Calhoun, Michael E.
Publikováno v:
In Journal of the American College of Radiology February 2023 20(2):232-242