Scalable analysis of multi-modal biomedical data.

ABSTRACT:

Background

Targeted diagnosis and treatment options are dependent on insights drawn from multi-modal analysis of large-scale biomedical datasets. Advances in genomics sequencing, image processing, and medical data management have supported data collection and management within medical institutions. These efforts have produced large-scale datasets and have enabled integrative analyses that provide a more thorough look of the impact of a disease on the underlying system. The integration of large-scale biomedical data commonly involves several complex data transformation steps, such as combining datasets to build feature vectors for learning analysis. Thus, scalable data integration solutions play a key role in the future of targeted medicine. Though large-scale data processing framew

SUBMITTER: Smith J 

PROVIDER: S-EPMC8434767 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature