As biomedical research has embraced the era of big data, massive amounts of complex multi-omic data are being generated. While there is huge potential in using the rich body of data to make new discoveries, many challenges exist in the dissemination, discovery, and reuse of these data. Artificial Intelligence (AI) and machine learning (ML) technologies have been paramount towards fully extracting value from rich and complex datasets to drive scientific discoveries and clinical decision-making. However, the adoption of AI and ML in endocrinology and metabolic diseases is lagging behind, compared to fields such as cancer genomics
Bibliographical noteFunding Information:
CA would like to acknowledge The Alan Turing Institute for a Network Development Award, grant TNDC2-100022, and Turing Network Funding, grant D-ELA-013.