An Interpretable Model for Predicting Acute Myocardial Infarction in Distinct Patient Profiles
This study underscores the heterogeneity of AMI patients and the importance of integrating patient profiles with biochemical markers for improved stratification in diagnosis and treatment. These identified profiles can guide personalised treatment strategies, tailoring interventions to the specific needs of each group. Understanding these profiles may also lead to novel therapeutic targets.
Authors
- Anthony Onoja (ORCID: https://orcid.org/0000-0002-1429-0032)
- Abdullah Zahid
- Nophar Geifman (ORCID: https://orcid.org/0000-0003-2956-6676)
- Kaisa Elomaa (ORCID: https://orcid.org/0000-0003-1167-699X)
Institutions
- University of Surrey (GB)
Publication Details
- Journal
- Studies in health technology and informatics
- Published
- 2025-05-15
- DOI
- https://doi.org/10.3233/shti250378
- Primary Topic
- Cardiovascular Function and Risk Factors
- Type
- article
- Field-Weighted Citation Impact
- 0.00