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Epidemiology

Cancer genetics

Alternative to Federated Learning in Medical Imaging: Categorical and Phenotypic Image Synthetic Learning

Researchers from the University of Texas Southwestern Medical Center have developed a novel method, Categorical and Phenotypic Image Synthetic Learning (CATphishing), to address the challenges of traditional federated learning in medical imaging. This innovative approach uses Latent Diffusion Models to generate synthetic multi-contrast three-dimensional magnetic resonance imaging data, eliminating the

Enzyme-linked immunosorbent assay

Development and Validation of a Double-Antibody Sandwich ELISA for Detection of Anguillid Herpesvirus

Researchers from the Fujian Academy of Agricultural Sciences in Fuzhou, People's Republic of China, have developed a new diagnostic tool for detecting Anguillid Herpesvirus (AngHV), a highly pathogenic agent causing 'Mucus sloughing and hemorrhagic septicemia disease' in eels. The double-antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA) was

Cancer genetics

Alternative to Federated Learning in Medical Imaging: Categorical and Phenotypic Image Synthetic Learning

Researchers from the University of Texas Southwestern Medical Center have developed a novel method, Categorical and Phenotypic Image Synthetic Learning (CATphishing), to address the challenges of traditional federated learning in medical imaging. This innovative approach uses Latent Diffusion Models to generate synthetic multi-contrast three-dimensional magnetic resonance imaging data, eliminating the

Cancer genetics

Alternative to Federated Learning in Medical Imaging: Categorical and Phenotypic Image Synthetic Learning

Researchers from the University of Texas Southwestern Medical Center have developed a novel method, Categorical and Phenotypic Image Synthetic Learning (CATphishing), to address the challenges of traditional federated learning in medical imaging. This innovative approach uses Latent Diffusion Models to generate synthetic multi-contrast three-dimensional magnetic resonance imaging data, eliminating the
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