Enhancing decision-making in tubal ectopic pregnancy using a machine learning approach to expectant management: a clinical article
The Decision Tree-Based classifier model, with 92% precision and 95% recall, may be a valuable tool for predicting treatment success in hemodynamically stable patients with EP, particularly within the initial 24 h of βhCG follow-up.
Authors
- Omer Weitzner (ORCID: https://orcid.org/0000-0001-6176-4424)
- Ron Schonman (ORCID: https://orcid.org/0000-0002-6317-3123)
- Karin Brisker
- Yael Yagur (ORCID: https://orcid.org/0000-0002-3560-6374)
- Yair Daykan (ORCID: https://orcid.org/0000-0002-0447-2414)
- Liron Jurman
- Zvi Klein
- Raz Ruach Hasdai
Institutions
- Tel Aviv University (IL)
- Meir Medical Center (IL)
- Microsoft (Israel) (IL)
Publication Details
- Journal
- BMC Pregnancy and Childbirth
- Published
- 2024-12-19
- DOI
- https://doi.org/10.1186/s12884-024-07035-4
- Citations
- 3
- Primary Topic
- Ectopic Pregnancy Diagnosis and Management
- Type
- article
- Field-Weighted Citation Impact
- 1.63