#AAAI2022 workshops round-up 1: AI to accelerate science and engineering, interactive machine learning, and health intelligence

Eran Halperin, SVP of AI and Machine Learning in Optum Labs and a professor in the departments of Computer Science, Computational Medicine, Anaesthesiology, and Human Genetics at UCLA, gave a keynote talk on using whole-genome methylation patterns as a biomarker for electronic health record (EHR) imputation. Dr Halperin showed that methylation provides a better imputation performance when compared to genetic or EHR data. This approach uses a new tensor deconvolution of bulk DNA methylation to obtain cell-type-specific methylation that is in turn used for imputation. Irene Chen from the Massachusetts Institute of Technology (MIT) gave a keynote describing how to leverage machine learning towards equitable healthcare. Dr Chen demonstrated how to adapt disease progression modeling to account for differences in access to care.