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Aims and scope

Aims and scope

BioData Mining is an open access, open peer-reviewed, informatics journal encompassing research on all aspects of Artificial Intelligence (AI), Machine Learning, and Visual Analytics, applied to high-dimensional biological and biomedical data, focusing on computational aspects of knowledge discovery from large-scale genetic, genomic, metabolomic data and/or electronic health records, social determinants of health, and environmental exposure data.

Topical areas include, but are not limited to:

  • Development, evaluation, and application of novel data mining and machine learning algorithms.
  • Adaptation, evaluation, and application of traditional data mining and machine learning algorithms.
  • Open-source software for the application of data mining and machine learning algorithms.
  • Design, development and integration of databases, software and web services for the storage, management, retrieval, and analysis of data from large scale studies.
  • Pre-processing, post-processing, modeling, and interpretation of data mining and machine learning results for biological interpretation and knowledge discovery.

Data types include

  • Imaging
  • Electronic health records
  • Biobanks
  • Environmental data
  • Social and behavioral data
  • Wearable devices
  • Social media data

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