Machine learning for cardio-oncology: predicting global longitudinal strain from conventional echocardiographic measurements in cancer patients
This study indicated the possibility that Low-GLS might be predicted by machine learning models from conventional echocardiography measurements in cancer patients.
Authors
- Tagayasu Anzai (ORCID: https://orcid.org/0000-0002-8529-2879)
- Kohsuke Kudo (ORCID: https://orcid.org/0000-0001-5351-9242)
- Ken Kato (ORCID: https://orcid.org/0000-0001-6993-5152)
- Kenji Hirata (ORCID: https://orcid.org/0000-0003-0036-8975)
Institutions
- Sapporo University (JP)
- Hokkaido University (JP)
- Hokkaido University Hospital (JP)
- Tokyo Metropolitan Tama Medical Center (JP)
Publication Details
- Journal
- Cardio-Oncology
- Published
- 2025-05-22
- DOI
- https://doi.org/10.1186/s40959-025-00348-z
- Citations
- 1
- Primary Topic
- Cardiovascular Function and Risk Factors
- Type
- article
- Field-Weighted Citation Impact
- 1.39