An adaptable LSTM trained with two optimizing algorithms instead of the back propagation learning algorithm is presented. The optimization algorithms are biogeography-based optimization (BBO) and genetic algorithm (GA). Dataset is collected locally and another benchmark dataset is used as well. Finally, the datasets fed into adaptable models; LSTM with BBO (LSTMBBO) and LSTM with GA (LSTMGA) for classification purposes. The experimental and testing results are compared and they are promising. This system helps physicians and doctors to provide proper health treatment for patients with diabetes mellitus.
Cite as
Rashid, T., Hassan, M., Mohammed, M. & Fraser, K. (2019), "Improvement of variant adaptable LSTM trained with metaheuristic algorithms for health care analysis", in Chakraborty, C. (Ed), Advanced Classification Techniques for Healthcare Analysis, IGI Global, Hershey, PA, Chapter 6, ISBN: 978-1-52257-796-6 DOI: 10.4018/978-1-5225-7796-6 https://www.igi-global.com/chapter/improvement-of-variant-adaptable-lstm-trained-with-metaheuristic-algorithms-for-healthcare-analysis/222143