Zobrazeno 1 - 10
of 354
pro vyhledávání: '"Mahmood, Tanveer"'
Autor:
Mahmood, Razi, Yan, Pingkun, Reyes, Diego Machado, Wang, Ge, Kalra, Mannudeep K., Kaviani, Parisa, Wu, Joy T., Syeda-Mahmood, Tanveer
Several evaluation metrics have been developed recently to automatically assess the quality of generative AI reports for chest radiographs based only on textual information using lexical, semantic, or clinical named entity recognition methods. In thi
Externí odkaz:
http://arxiv.org/abs/2412.01031
Autor:
Kashyap, Satyananda, D'Souza, Niharika S., Shi, Luyao, Wong, Ken C. L., Wang, Hongzhi, Syeda-Mahmood, Tanveer
Content-addressable memories such as Modern Hopfield Networks (MHN) have been studied as mathematical models of auto-association and storage/retrieval in the human declarative memory, yet their practical use for large-scale content storage faces chal
Externí odkaz:
http://arxiv.org/abs/2409.16408
Autor:
Chen, Yiming, D'Souza, Niharika S., Mandepally, Akshith, Henninger, Patrick, Kashyap, Satyananda, Karani, Neerav, Dey, Neel, Zachary, Marcos, Rizq, Raed, Chouinard, Paul, Golland, Polina, Syeda-Mahmood, Tanveer F.
Precisely estimating lumen boundaries in intravascular ultrasound (IVUS) is needed for sizing interventional stents to treat deep vein thrombosis (DVT). Unfortunately, current segmentation networks like the UNet lack the precision needed for clinical
Externí odkaz:
http://arxiv.org/abs/2408.04826
Autor:
Wong, Ken C. L., Klein, Levente, da Silva, Ademir Ferreira, Wang, Hongzhi, Singh, Jitendra, Syeda-Mahmood, Tanveer
Soil organic carbon (SOC) sequestration is the transfer and storage of atmospheric carbon dioxide in soils, which plays an important role in climate change mitigation. SOC concentration can be improved by proper land use, thus it is beneficial if SOC
Externí odkaz:
http://arxiv.org/abs/2311.13016
Autor:
Warner, Elisa, Lee, Joonsang, Hsu, William, Syeda-Mahmood, Tanveer, Kahn, Charles, Gevaert, Olivier, Rao, Arvind
Machine learning (ML) applications in medical artificial intelligence (AI) systems have shifted from traditional and statistical methods to increasing application of deep learning models. This survey navigates the current landscape of multimodal ML,
Externí odkaz:
http://arxiv.org/abs/2311.02332
With the introduction of Transformers, different attention-based models have been proposed for image segmentation with promising results. Although self-attention allows capturing of long-range dependencies, it suffers from a quadratic complexity in t
Externí odkaz:
http://arxiv.org/abs/2310.04466
Due to the computational complexity of 3D medical image segmentation, training with downsampled images is a common remedy for out-of-memory errors in deep learning. Nevertheless, as standard spatial convolution is sensitive to variations in image res
Externí odkaz:
http://arxiv.org/abs/2310.03872
Autor:
D'Souza, Niharika S., Wang, Hongzhi, Giovannini, Andrea, Foncubierta-Rodriguez, Antonio, Beck, Kristen L., Boyko, Orest, Syeda-Mahmood, Tanveer
With the emergence of multimodal electronic health records, the evidence for an outcome may be captured across multiple modalities ranging from clinical to imaging and genomic data. Predicting outcomes effectively requires fusion frameworks capable o
Externí odkaz:
http://arxiv.org/abs/2307.07093