Then, the processing occurred in two steps, namely, format conversion and data transformation. ![]() The proposed model involved preprocessing, artificial flora algorithm (AFA)-based feature selection, and gradient boosted tree (GBT)-based classification. Methods: Three different datasets are used to develop a novel medical data classification model. Purpose: Classification of medical data is essential to determine diabetic treatment options therefore, the objective of the study was to develop a model to classify the three diabetes type diagnoses according to multiple patient attributes. Nagaraj P, 1 Deepalakshmi P, 1 Romany F Mansour, 2 Ahmed Almazroa 3ġDepartment of Computer Science and Engineering, School of Computing, Kalasalingam Academy of Research and Education, Virudhunagar, Tamil Nadu, India 2Department of Mathematics, Faculty of Science, New Valley University, El-Kharga, Egypt 3Department of imaging Research, King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Science, Riyadh, Saudi Arabiaĭepartment of Computer Science and Engineering, School of Computing, Kalasalingam Academy of Research and Education, Anand Nagar, Krishnankoil, Srivilliputtur, Virudhunagar, Tamil Nadu, 626126, India
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