Machine Learning Models for Classification of Anemia from CBC Results: Random Forest, SVM, and Logistic Regression

• Main Authors: Muhammad Rafli, Aditya, Teguh, Sutanto, Haldi, Budiman, M.Rezqy, Noor Ridha, Usman, Syapotro, Noor, Azijah
• Format: Article
• Language: English; English
• Published: INTI International University 2024
• Subjects: QA75 Electronic computers. Computer science; QA76 Computer software; T Technology (General)
• Online Access: http://eprints.intimal.edu.my/2048/1/jods2024_49.pdf; http://eprints.intimal.edu.my/2048/2/589; http://eprints.intimal.edu.my/2048/; http://ipublishing.intimal.edu.my/jods.html

In an effort to increase diagnostic efficiency and accuracy, this work investigates the application of machine learning models Random Forest, SVM, and Logistic Regression for the categorization of anemia. Hematocrit and hemoglobin levels were included in the dataset, which was divided into traini...