Faculty, Staff and Student Publications
Language
English
Publication Date
1-1-2024
Journal
Global Challenges
DOI
10.1002/gch2.202300163
PMID
38223896
PMCID
PMC10784210
PubMedCentral® Posted Date
11-20-2023
PubMedCentral® Full Text Version
Post-print
Abstract
The explosive growth of biomedical Big Data presents both significant opportunities and challenges in the realm of knowledge discovery and translational applications within precision medicine. Efficient management, analysis, and interpretation of big data can pave the way for groundbreaking advancements in precision medicine. However, the unprecedented strides in the automated collection of large-scale molecular and clinical data have also introduced formidable challenges in terms of data analysis and interpretation, necessitating the development of novel computational approaches. Some potential challenges include the curse of dimensionality, data heterogeneity, missing data, class imbalance, and scalability issues. This overview article focuses on the recent progress and breakthroughs in the application of big data within precision medicine. Key aspects are summarized, including content, data sources, technologies, tools, challenges, and existing gaps. Nine fields-Datawarehouse and data management, electronic medical record, biomedical imaging informatics, Artificial intelligence-aided surgical design and surgery optimization, omics data, health monitoring data, knowledge graph, public health informatics, and security and privacy-are discussed.
Keywords
biomedical big data, electronic medical record, federated learning, knowledge graph, medical imaging analysis, omics data, precision medicine
Published Open-Access
yes
Recommended Citation
Yang, Xue; Huang, Kexin; Yang, Dewei; et al., "Biomedical Big Data Technologies, Applications, and Challenges for Precision Medicine: A Review" (2024). Faculty, Staff and Student Publications. 879.
https://digitalcommons.library.tmc.edu/uthshis_docs/879