Transitions of Frail Seniors across the Spectrum of Healthcare

Kejriwal, Kamal; Israel, Beth; Wilde, Ginny

doi:10.1016/j.jamda.2009.12.075

Cited by 1 publication

(1 citation statement)

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“…With the increasing application of knowledge graphs, [ 208 ] many researchers have extracted information from medical databases and then constructed heterogeneous knowledge graphs about medicines and diseases. For instance, DrugBank is a rich source of medical information, and it contains a wide range of entities (drugs, drug targets, chemistry, etc.)…”

Section: Knowledge Graph For Precision Medicinementioning

confidence: 99%

Biomedical Big Data Technologies, Applications, and Challenges for Precision Medicine: A Review

Yang,

Huang,

Yang

et al. 2023

Global Challenges

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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.

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Section: Knowledge Graph For Precision Medicinementioning

confidence: 99%