Ahmed, M., Zaghloul, I., Abd El Fattah, M. (2023). A Survey on Personalization of Diabetes Treatment using Artificial Intelligence Techniques. Benha Journal of Applied Sciences, 8(5), 229-236. doi: 10.21608/bjas.2023.202990.1140
Maryam Gaber Ahmed; Ibrahim Zaghloul; Mohamed Taha Abd El Fattah. "A Survey on Personalization of Diabetes Treatment using Artificial Intelligence Techniques". Benha Journal of Applied Sciences, 8, 5, 2023, 229-236. doi: 10.21608/bjas.2023.202990.1140
Ahmed, M., Zaghloul, I., Abd El Fattah, M. (2023). 'A Survey on Personalization of Diabetes Treatment using Artificial Intelligence Techniques', Benha Journal of Applied Sciences, 8(5), pp. 229-236. doi: 10.21608/bjas.2023.202990.1140
Ahmed, M., Zaghloul, I., Abd El Fattah, M. A Survey on Personalization of Diabetes Treatment using Artificial Intelligence Techniques. Benha Journal of Applied Sciences, 2023; 8(5): 229-236. doi: 10.21608/bjas.2023.202990.1140
A Survey on Personalization of Diabetes Treatment using Artificial Intelligence Techniques
1Computer science, faculty of computers and artificial intelligence, Benha univercity
2Computer Science Dept., Faculty of Computers & Artificial Intelligence, Benha University
Abstract
Diabetes mellitus is a disease caused by uncontrolled diabetes that can lead to multiple organ failure in patients. Thanks to advances in artificial intelligence, the diagnosis and early detection of diabetic disease is possible. Many articles are currently being published on the use of artificial intelligence and machine learning techniques for automated detection, diagnosis, and personalized treatment and management of diabetes. This survey analyzed technologies for the personalized treatment of diabetes from five different perspectives: blood glucose prediction, Glycemic variability detection, Hyperglycemia detection, Insulin controller therapy, and Pharmacogenetics. Diabetes treatment depends on medical, demographic, and lifestyle parameters. These parameters included diabetes type, age, body weight, duration of diabetes, comorbidities, blood sugar, physical activity, and diet. Artificial intelligence is considered a useful technology to support diabetes treatment. This survey provides a detailed overview of Diabetes detection and personalized treatment techniques which may be very useful to the community of scientists in automatic Diabetes detection and personalized treatment for diabetes.
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