Abstract: A machine-learning (ML) model may be trained to receive, as input, epigenetic data associated with a subject and to output a continuous value and/or a classification of a biochemical state and/or medical condition associated with a subject. For example, the biochemical state and/or medical condition may comprise an indication that the subject consumes alcohol and/or nicotine and/or that the subject is diabetic or is likely to become diabetic, to give a small non-limiting example. The epigenetic data may be derived from saliva and/or blood in some examples.

Abstract: A machine learning (ML) architecture may be trained to determine an estimated epigenetic status at a target DNA locus based at least in part on epigenetic data associated with one or more other DNA loci. The ML architecture may additionally or alternatively be used to detect a failed epigenetic assay and/or determine a likelihood that a subject has falsified information provided about the subject.