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Artificial intelligence, physiological genomics, and precision medicine.

Anna Marie Williams1, Yong Liu1, Kevin R Regner2

  • 1Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin , Milwaukee, Wisconsin.

Physiological Genomics
|January 27, 2018
PubMed
Summary

Machine learning (ML) and artificial intelligence (AI) are key to precision medicine. Using relevant data from disease-applicable tissues, like kidney biopsies, enhances ML accuracy for common diseases.

Keywords:
artificial intelligencefunctional genomicsmachine learningphysiological genomicsprecision medicine

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Area of Science:

  • Biomedical Informatics
  • Genomics
  • Artificial Intelligence

Background:

  • Big data analytics are crucial for advancing precision medicine.
  • Machine learning (ML), a subset of artificial intelligence (AI), offers powerful tools for analyzing complex biological data.
  • Current ML approaches in precision medicine often prioritize data quantity over quality and relevance.

Purpose of the Study:

  • To highlight the importance of data relevance and accuracy in ML for precision medicine.
  • To propose physiological genomic readouts in disease-applicable tissues as a valuable data source.
  • To emphasize the need for advanced AI analytical approaches and ethical considerations.

Main Methods:

  • Review of current ML and AI applications in precision medicine.
  • Discussion of the role of genomic data and electronic health records.
  • Exploration of physiological genomic readouts in disease-relevant tissues as surrogate data.

Main Results:

  • Data relevance and accuracy are as critical as data quantity for effective ML in precision medicine.
  • Physiological genomic readouts from accessible tissues (e.g., kidney biopsies) can effectively capture genetic and environmental influences on common diseases.
  • Advanced AI methods beyond simple correlation are needed, alongside ethical frameworks.

Conclusions:

  • Integrating physiological genomic data from relevant tissues with advanced AI offers a potent strategy for precision medicine in common diseases.
  • Kidney needle biopsies represent a practical source for such data.
  • Future research should focus on developing novel AI analytical techniques and addressing ethical concerns.