Analyzing Diabetic Dynamics with MRK4, and LSTM Techniques with Multiplicative Calculus
Abstract
Keywords
Neural network, Runge kutta, Multiplicative calculus, Long Short-Term Memory, Dabetes.
References
- [1] Emerging Risk Factors Collaboration, Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies, The lancet, 375(9733) (2010) 2215-222
- [2] Ramsingh J., & Bhuvaneswari V. (2021). An efficient map reduce-based hybrid NBC-TFIDF algorithm to mine the public sentiment on diabetes mellitus–a big data approach, Journal of King Saud University-Computer and Information Sciences, 33(8) 1018-1029.
- [3] Artzi N. S., Shilo, S., Hadar E., Rossman H., Barbash-Hazan S., Ben-Haroush A., ... , Segal E., Prediction of gestational diabetes based on nationwide electronic health records. Nature medicine, 26(1) (2020), 71-76.
- [4] Misra A., Gopalan H., Jayawardena R., Hills A. P., Soares M., Reza‐Albarrán A. A., Ramaiya K. L., Diabetes in developing countries. Journal of diabetes, 11(7) (2019) 522-539.
- [5] Edwards M. S., Wilson D. B., Craven T. E., Stafford J., Fried L. F., Wong T. Y., ... , Hansen K. J., Associations between retinal microvascular abnormalities and declining renal function in the elderly population: the Cardiovascular Health Study. American journal of kidney diseases, 46(2) (2005) 214-224.
- [6] Saeedi P., Petersohn I., Salpea P., Malanda B., Karuranga S., Unwin N., et all., IDF Diabetes Atlas CommitteeGlobal and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, Diabetes research and clinical practice, 157 (2019) 107843.
- [7] Vaishali R., Sasikala R., Ramasubbareddy S., Remya S., Nalluri SGenetic algorithm based feature selection and MOE Fuzzy classification algorithm on Pima Indians Diabetes dataset. In 2017 international conference on computing networking and informatics (ICCNI), (2017) 1-5.
- [8] Cho N. H., Shaw J. E., Karuranga S., Huang Y., da Rocha Fernandes J. D., Ohlrogge,A. W., Malanda, B. I. D. F., IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045, Diabetes research and clinical practice, 138 (2018) 271-281.
- [9] Maniruzzaman M., Rahman M. J., Al-MehediHasanM., Suri, H. S., Abedin, M. M., El-Baz A., Suri J. S., Accurate diabetes risk stratification using machine learning: role of missing value and outliers. Journal of medical systems, 42 (2018) 1-17.
- [10] Brahim-Belhouari S., Bermak A., Gaussian process for nonstationary time series prediction, Computational Statistics & Data Analysis, 47(4) (2004) 705-712.