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The main objective of this research is to predict the possible presence of diabetes -specifically in females-at an early stage using different machine learning techniques. Early detection of diabetes can significantly prevent the progression of the disease and reduce the risk of serious complications such as heart and kidney diseases, making the proper lifestyle changes at the right time can help avoid diabetes and all the illnesses associated with it. So, there is a crucial need for a tool that can better assist doctors to detect this deadly disease at an early stage and consequently stop its progression. Finally, this model produced an accuracy of 82% based on the random forest classifier model.
Abdulhadi et al. (Wed,) studied this question.