World models for biomedicine.

Ayush Noori¹, Nic Fishman², Ada Fang³, Lukas Fesser⁴, Marinka Zitnik⁵

¹Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Department of Engineering Science, University of Oxford, Oxford, UK.

²Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Department of Statistics, Harvard University, Cambridge, MA, USA.

³Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA; Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University, Allston, MA, USA.

⁴Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University, Allston, MA, USA; Applied Mathematics, Harvard John A. Paulson School of Engineering and Applied Sciences, Allston, MA, USA.

⁵Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University, Allston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Data Science Initiative, Cambridge, MA, USA. Electronic address: marinka@hms.harvard.edu.

PubMed DOI

Abstract

Biological systems respond dynamically to changes in their environment, and predicting these responses before complex interventions are applied could change how computational models are used in biology and medicine. In artificial intelligence, world models represent the state of a system and simulate how it evolves under alternative actions. We envision extending this paradigm to biomedicine, with…

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