Assistant Professor of Biomedical Informatics, Harvard Medical School @HarvardDBMI | Founding Deputy Editor, @NEJM_AI | Co-host, NEJM AI Grand Rounds
2/ First, a huge shoutout to our superstar co-first authors @PeterBrodeurMD (IM resident @BIDMC_IM) and @tabuckley_ (PhD student in @AIM_Harvard_PhD). Without them this paper would not exist.
Some background: Inspired by Genome Wide Association Studies (GWASs), 'X-WASs' have emerged as systematic, agnostic, and reproducible approaches to discovery with non-genetic data (e.g. X = Environment, Medication, Phenotypes...etc.) For ex., the EWAS by @chiragjp et al. 2/n 