Classification of anemic condition based on photoplethysmography signals and clinical dataset
Ultimately, this proposed ML model in this paper validated the effectiveness of the ML algorithms as non-invasive techniques for identifying Anemia.
Authors
- Neven Saleh (ORCID: https://orcid.org/0000-0002-6304-9819)
- Ahmed M. Salaheldin (ORCID: https://orcid.org/0000-0002-4776-8872)
- Heba M. Afify (ORCID: https://orcid.org/0000-0002-6279-0883)
- Yasser Ismail (ORCID: https://orcid.org/0000-0001-6648-6275)
Institutions
- Southern University and Agricultural and Mechanical College (US)
- Future University in Egypt (EG)
- El Shorouk Academy (EG)
Publication Details
- Journal
- Biomedizinische Technik/Biomedical Engineering
- Published
- 2025-04-08
- DOI
- https://doi.org/10.1515/bmt-2024-0433
- Citations
- 5
- Primary Topic
- Non-Invasive Vital Sign Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 3.37