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Artificial Intelligence Approaches in Diabetic Prediction

Artificial Intelligence Approaches in Diabetic Prediction

Sabitha E.
Copyright: © 2023 |Pages: 27
ISBN13: 9781668469378|ISBN10: 1668469375|ISBN13 Softcover: 9781668469385|EISBN13: 9781668469392
DOI: 10.4018/978-1-6684-6937-8.ch021
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MLA

E., Sabitha. "Artificial Intelligence Approaches in Diabetic Prediction." Handbook of Research on AI Methods and Applications in Computer Engineering, edited by Sanaa Kaddoura, IGI Global, 2023, pp. 451-477. https://doi.org/10.4018/978-1-6684-6937-8.ch021

APA

E., S. (2023). Artificial Intelligence Approaches in Diabetic Prediction. In S. Kaddoura (Ed.), Handbook of Research on AI Methods and Applications in Computer Engineering (pp. 451-477). IGI Global. https://doi.org/10.4018/978-1-6684-6937-8.ch021

Chicago

E., Sabitha. "Artificial Intelligence Approaches in Diabetic Prediction." In Handbook of Research on AI Methods and Applications in Computer Engineering, edited by Sanaa Kaddoura, 451-477. Hershey, PA: IGI Global, 2023. https://doi.org/10.4018/978-1-6684-6937-8.ch021

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Abstract

Healthcare applications in monitoring and managing diseases have undergone rapid development in medical sectors and play an important in observing and controlling diabetes mellitus (DM). DM is a chronic infection that is caused by extreme blood sugar level. The rapid increase of DM world-wide have the effect of gaining attention to predict DM at early stage. Consequently, various technologies have been used to diagnose diabetes at an early stage to avoid major health defects. The most satisfaction in disease prediction and classification methods has been achieved through AI techniques and algorithms in healthcare. The main of the objective of the study is to provide a detail review on DM, the increase of DM around world-wide, datasets used in diabetic prediction, advance techniques and methods applied for disease prediction, and applications and its limitations used in diabetic prediction. The study also provides a detailed review on recent techniques and methods used in disease prediction, which guides the evolution of AI techniques and will provide a well-grounded knowledge of existing methods.

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