
Artificial intelligence in human genomics and biomedicine
Author(s) -
Reinhard Heil,
Nils B. Heyen,
Martina Baumann,
Bärbel Hüsing,
Daniel Bachlechner,
Ulrich Schmoch,
Harald König
Publication year - 2021
Publication title -
zeitschrift für technikfolgenabschätzung in theorie und praxis
Language(s) - English
Resource type - Journals
eISSN - 2568-020X
pISSN - 2567-8833
DOI - 10.14512/tatup.30.3.30
Subject(s) - biomedicine , genomics , artificial intelligence , computer science , domain (mathematical analysis) , convergence (economics) , data science , genome , bioinformatics , biology , mathematics , mathematical analysis , biochemistry , economics , gene , economic growth
The increasing availability of extensive and complex data has made human genomics and its applications in (bio)medicine an at tractive domain for artificial intelligence (AI) in the form of advanced machine learning (ML) methods. These methods are linked not only to the hope of improving diagnosis and drug development. Rather, they may also advance key issues in biomedicine, e. g. understanding how individual differences in the human genome may cause specific traits or diseases. We analyze the increasing convergence of AI and genomics, the emergence of a corresponding innovation system, and how these associative AI methods relate to the need for causal knowledge in biomedical research and development (R&D) and in medical practice. Finally, we look at the opportunities and challenges for clinical practice and the implications for governance issues arising from this convergence.