Machine learning based Diagnosis and Classification Of Sickle Cell Anemia in Human RBC
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Publisher
IEEE
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http://xplorestaging.ieee.org/ielx7/9388249/9388373/09388610.pdf?arnumber=9388610
Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Deep Learning-Based Red Blood Cell Classification for Sickle Cell Anemia Diagnosis Using Hybrid CNN-LSTM Model;Traitement du Signal;2024-06-26
2. Experimental study and comparison of medical methodology and machine learning models to enhance algorithms for morphological classification of clinical and hematologic syndromes;2024 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA);2024-05-23
3. Enhancing Disease Diagnosis: Statistical Analysis of Haematological Parameters in Sickle Cell Patients, Integrating Predictive Analytics;EAI Endorsed Transactions on Pervasive Health and Technology;2024-04-09
4. Cell classification in microscopic images for anemia detection;Revista Română de Informatică și Automatică;2024-03-29
5. Classification and Explanation of Iron Deficiency Anemia from Complete Blood Count Data Using Machine Learning;BioMedInformatics;2024-03-01
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