Statistical Analysis of Hematological Parameters for Prediction of Sickle Cell Disease
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-48888-7_7
Reference15 articles.
1. Chhotray, G.P., Dash, B.P., Ranjit, M.: Spectrum of Hemoglobinopathies in Orissa, India (2004). https://doi.org/10.1081/hem-120034244
2. Piel, F.B., et al.: Global distribution of the sickle cell gene and geographical confirmation of the malaria hypothesis (2010). https://doi.org/10.1038/ncomms1104
3. Serjeant, G.R.: One hundred years of sickle cell disease (2010). https://doi.org/10.1111/j.1365-2141.2010.08419.x
4. Meher, S., et al.: Haptoglobin Genotypes Associated with Vaso-Occlusive Crisis in Sickle Cell Anemia Patients of Eastern India (2021). https://doi.org/10.1080/03630269.2020.1801459
5. Sen, B., Ganesh, A., Bhan, A., Dixit, S., Goyal, A.: Machine learning based diagnosis and classification of sickle cell anemia in human RBC. In: 2021 Third International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV), Tirunelveli, India, pp. 753–758 (2021). https://doi.org/10.1109/ICICV50876.2021.9388610
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