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Abstract Identifying rare disease (RD) patients in electronic health records (EHRs) is difficult, as most of the over 10,000 RDs are not adequately captured by standard coding systems. To address this, we developed a semi-automated workflow to map RDs to SNOMED-CT and ICD-10 codes, enabling improved RD identification across EHR systems. The optimized workflow yielded 88.4% true RD codes in a subset of 1,715 manually curated diseases.

Abstract Biological aging reflects complex cellular and biochemical processes that can be measured across multiple omic layers. Using routine clinical laboratory data from ~31,000 participants in the Mass General Brigham Biobank, we developed EMRAge, a biomarker of mortality risk that can be broadly recapitulated across electronic medical records.

Journal of Proteome Research Cite this: J. Proteome Res. 2025, XXXX, XXX Click to copy citationCitation copied! . This publication is licensed under CC-BY-NC-ND 4.0 . You are free to share (copy and redistribute) this article in any medium or format within the parameters below: Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Non-Commercial (NC): Only non-commercial uses of the work are permitted.