Automating Digital Health

While artificial intelligence (AI) has become widespread, many commercial AI systems are not yet accessible to individual researchers nor the general public due to the deep knowledge of the systems required to use them. We believe that AI has matured to the point where it should be an accessible technology for everyone12. The ultimate goal of this research area is to develop AI systems that automate the entire computational workflows of today’s data scientists3. Doing will accelerate the analysis of complex data in the biomedical and health care domains4.

Overview of the PennAI GUI
Accessible, Automatic Data Science: github.com/EpistasisLab/Aliro

References

  1. Randal S Olson, Moshe Sipper, William La Cava, Sharon Tartarone, Steven Vitale, Weixuan Fu, John H Holmes, Jason H. Moore (2017). A System for Accessible Artificial Intelligence. Genetic Programming Theory and Practice XIV ↩

  2. Pearson, J. (2017). These Researchers Want the People to Seize the Means of AI Production. Motherboard. link ↩

  3. William La Cava, Heather Williams, Weixuan Fu, Steve Vitale, Durga Srivatsan, Jason H Moore (2020). Evaluating recommender systems for AI-driven biomedical informatics. Bioinformatics ↩

  4. See my post talking about our Bioinformatics paper. ↩

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