Predicting Individual Treatment Effects to Determine Duration of Dual Antiplatelet Therapy After Stent Implantation
Machine learning using the X-learner approach identifies patients with acute coronary syndrome who may benefit from abbreviated DAPT after drug-eluting stent implantation, laying the groundwork for personalized antiplatelet therapy.
Authors
- Byeong‐Keuk Kim (ORCID: https://orcid.org/0000-0003-2493-066X)
- Sung‐Jin Hong (ORCID: https://orcid.org/0000-0003-4893-039X)
- Donghoon Choi (ORCID: https://orcid.org/0000-0002-2009-9760)
- Myeong‐Ki Hong (ORCID: https://orcid.org/0000-0002-2090-2031)
- Seng Chan You (ORCID: https://orcid.org/0000-0002-5052-6399)
- Jaehyeong Cho (ORCID: https://orcid.org/0000-0001-7213-5033)
- Young‐Guk Ko (ORCID: https://orcid.org/0000-0001-7748-5788)
- Chul‐Min Ahn (ORCID: https://orcid.org/0000-0002-7071-4370)
- Seung‐Jun Lee (ORCID: https://orcid.org/0000-0002-9201-4818)
- Jung‐Sun Kim (ORCID: https://orcid.org/0000-0003-2263-3274)
- Ji Hye Shin (ORCID: https://orcid.org/0000-0002-8157-8618)
Institutions
- Yonsei University (KR)
- Severance Hospital (KR)
- Health Insurance Review and Assessment Service (KR)
- Keimyung University Dongsan Medical Center (KR)
- Gangnam Severance Hospital (KR)
- Keimyung University (KR)
Publication Details
- Journal
- Journal of the American Heart Association
- Published
- 2024-09-30
- DOI
- https://doi.org/10.1161/jaha.124.034862
- Citations
- 1
- Primary Topic
- Antiplatelet Therapy and Cardiovascular Diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.40
Funders
- Yonsei University
- Yonsei University College of Medicine