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. 2023 Jul 29;6:135. doi: 10.1038/s41746-023-00879-8

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 1 — Overview of the inputs and outputs of the two main types of clinical FMs. a The inputs and outputs of Clinical Language Models (CLaMs). CLaMs ingest clinical text and output either clinical text or a machine-understandable representation of the input text, which can then be used for downstream prediction tasks. b The inputs and outputs of Foundation models for Electronic Medical Records (FEMRs). FEMRs ingest a patient’s medical history—which is simply a sequence of medical events with some temporal ordering—and output a machine-understandable representation of the patient, which can then be used for downstream prediction tasks.