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Training Neural Networks as Experimental Models: Classifying Biomedical Datasets for Sickle Cell Disease.

, , , , , , , , and . ICIC (1), volume 9771 of Lecture Notes in Computer Science, page 784-795. Springer, (2016)

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Predicting Freezing of Gait in Parkinsons Disease Patients Using Machine Learning., , , , , and . CEC, page 1-8. IEEE, (2018)The Application of Gaussian Mixture Models for the Identification of At-Risk Learners in Massive Open Online Courses., , , , and . CEC, page 1-8. IEEE, (2018)Towards the discrimination of primary and secondary headache: An intelligent systems approach., , , , and . IJCNN, page 2768-2775. IEEE, (2017)Applied Difference Techniques of Machine Learning Algorithm and Web-Based Management System for Sickle Cell Disease., , , , , , and . DeSE, page 231-235. IEEE, (2015)Machine learning approaches to predict learning outcomes in Massive open online courses., , , , , and . IJCNN, page 713-720. IEEE, (2017)Students Performance Prediction in Online Courses Using Machine Learning Algorithms., , , and . IJCNN, page 1-7. IEEE, (2020)Analyzing Learners Behavior in MOOCs: An Examination of Performance and Motivation Using a Data-Driven Approach., , , and . IEEE Access, (2018)An Intelligent Systems Approach to Primary Headache Diagnosis., , , , , and . ICIC (2), volume 10362 of Lecture Notes in Computer Science, page 61-72. Springer, (2017)Detecting At-Risk Students With Early Interventions Using Machine Learning Techniques., , , and . IEEE Access, (2019)Artificial Intelligence for Detecting Preterm Uterine Activity in Gynecology and Obstetric Care., , , , , , and . CIT/IUCC/DASC/PICom, page 215-220. IEEE, (2015)