Presenting a prediction model for HELLP syndrome through data mining
The present work indicated that ML algorithms can be used successfully in the development of HELLP syndrome diagnosis models. Other algorithms besides DTs have an F1 score above 0.90. In addition, this study demonstrated that biomarker features (among all features) have the most significant impact on the diagnosis of HELLP syndrome.
Authors
- Ladan Ajori (ORCID: https://orcid.org/0000-0003-4818-338X)
- Mohammadjavad Sayadi (ORCID: https://orcid.org/0000-0003-1511-8725)
- Boshra Farajollahi
- Mostafa Langarizadeh (ORCID: https://orcid.org/0000-0003-2965-5038)
Institutions
- University of Applied Science and Technology (IR)
- Shahid Beheshti University of Medical Sciences (IR)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2025-03-17
- DOI
- https://doi.org/10.1186/s12911-025-02904-0
- Citations
- 1
- Primary Topic
- Cancer-related molecular mechanisms research
- Type
- article
- Field-Weighted Citation Impact
- 0.94