Explainable temporal machine learning of multimorbidity trajectories after acute myocardial infarction: complementing clinical risk scores with mechanistic phenotypes

Anthony Onoja, Kris Elomaa, Anthony D Whetton, Nophar Geifman

Open source

DOI
10.1093/jamia/ocag135
Published
2026-08-06
Container
Journal of the American Medical Informatics Association
Publisher
Oxford University Press (OUP)
Open access
unknown

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BibTeX

@article{allodium:10.1093/jamia/ocag135,
  title = {Explainable temporal machine learning of multimorbidity trajectories after acute myocardial infarction: complementing clinical risk scores with mechanistic phenotypes},
  author = {Anthony Onoja and Kris Elomaa and Anthony D Whetton and Nophar Geifman},
  year = {2026},
  journal = {Journal of the American Medical Informatics Association},
  doi = {10.1093/jamia/ocag135},
  url = {https://doi.org/10.1093/jamia/ocag135}
}

RIS

TY  - JOUR
TI  - Explainable temporal machine learning of multimorbidity trajectories after acute myocardial infarction: complementing clinical risk scores with mechanistic phenotypes
AU  - Anthony Onoja
AU  - Kris Elomaa
AU  - Anthony D Whetton
AU  - Nophar Geifman
PY  - 2026
JO  - Journal of the American Medical Informatics Association
DO  - 10.1093/jamia/ocag135
UR  - https://doi.org/10.1093/jamia/ocag135
ER  - 

APA

Onoja, A., Elomaa, K., Whetton, A. D., & Geifman, N. (2026). Explainable temporal machine learning of multimorbidity trajectories after acute myocardial infarction: complementing clinical risk scores with mechanistic phenotypes. Journal of the American Medical Informatics Association. https://doi.org/10.1093/jamia/ocag135

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