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Multi-modal trained artificial intelligence solution to triage chest X-ray for COVID-19 using pristine ground-truth, versus radiologists.

, , , , , , , , , , , , , , , , and . Neurocomputing, (2022)

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SonoSAM - Segment Anything on Ultrasound Images., , , and . ASMUS@MICCAI, volume 14337 of Lecture Notes in Computer Science, page 23-33. Springer, (2023)Accelerated Cartesian expansion (ACE) based framework for the rapid evaluation of diffusion, lossy wave, and Klein-Gordon potentials., , , and . J. Comput. Phys., 229 (24): 9119-9134 (2010)Pristine annotations-based multi-modal trained artificial intelligence solution to triage chest X-ray for COVID-19., , , , , , , , , and 6 other author(s). CoRR, (2020)Parallel accelerated cartesian expansions for particle dynamics simulations., , , and . IPDPS, page 1-11. IEEE, (2009)Pristine Annotations-Based Multi-modal Trained Artificial Intelligence Solution to Triage Chest X-Ray for COVID-19., , , , , , , , , and 6 other author(s). MICCAI (7), volume 12907 of Lecture Notes in Computer Science, page 325-334. Springer, (2021)Non-intrusive microwave system for multiphase flow metering., , , , and . I2MTC, page 1-6. IEEE, (2018)Causal Feature Alignment: Learning to Ignore Spurious Background Features., , , and . WACV, page 4654-4662. IEEE, (2024)Multi-modal trained artificial intelligence solution to triage chest X-ray for COVID-19 using pristine ground-truth, versus radiologists., , , , , , , , , and 7 other author(s). Neurocomputing, (2022)SonoSAM - Segment Anything on Ultrasound Images., , , , , and . CoRR, (2023)Water-Cut Estimation Uncertainty from Microwave Sensors., , , and . IEEE SENSORS, page 1-4. IEEE, (2018)