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Academic Publication AbdomenAtlas: A large-scale, detailed-annotated, & multi-center dataset for efficient transfer learning and open algorithmic benchmarking
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AbdomenAtlas: A large-scale, detailed-annotated, & multi-center dataset for efficient transfer learning and open algorithmic benchmarking
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A technical review of multi-omics data integration methods: from classical statistical to deep generative approaches
Abstract The rapid advancement of high-throughput sequencing and other assay technologies has resulted in the generation of large and complex multi-omics datasets, offering unprecede...
Deep learning-based approaches for multi-omics data integration and analysis
Abstract Background The rapid growth of deep learning, as well as the vast and ever-growing amount of available data, have provided ample opportunity for advances in...
Leveraging functional genomic annotations and genome coverage to improve polygenic prediction of complex traits within and between ancestries
Abstract We develop a method, SBayesRC, that integrates genome-wide association study (GWAS) summary statistics with functional genomic annotations to improve polygenic prediction...
Biomedical knowledge graph-optimized prompt generation for large language models
Abstract Motivation Large language models (LLMs) are being adopted at an unprecedented rate, yet still face challenges in knowledge-intensive dom...
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What is the core focus of the research titled 'AbdomenAtlas: A large-scale, detailed-annotated, & multi-center dataset for efficient transfer learning and open algorithmic benchmarking'?
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What other academic literature is closely related to 'AbdomenAtlas: A large-scale, detailed-annotated, & multi-center dataset for efficient transfer learning and open algorithmic benchmarking'?
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