Analytical model to predict diabetic patients using an optimized hybrid classifier-Reference-Cited by-同舟云学术

Analytical model to predict diabetic patients using an optimized hybrid classifier

Published:2023-12-18 Issue:3 Volume:28 Page:1883-1892
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Shimpi Jayanta Kiran,Shanmugam Poonkuntran,Stonier Albert Alexander^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s00500-023-09487-w.pdf

Reference38 articles.

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2. Alshamlan H, Taleb HB, Al Sahow A (2020) A gene prediction function for type 2 diabetes mellitus using logistic regression. In: 2020 11th International conference on information and communication systems (ICICS). IEEE, Irbid, Jordan, pp 1–4

3. Bakkouri I, Afdel K (2023) MLCA2F: multi-level context attentional feature fusion for COVID-19 lesion segmentation from CT scans. Signal Image Video Process 17(4):1181–1188. https://doi.org/10.1007/s11760-022-02325-w

4. Bakkouri I, Afdel K, Benois-Pineau J, GCFADN Initiative (2022) BG-3DM2F: bidirectional gated 3D multi-scale feature fusion for Alzheimer’s disease diagnosis. Multimed Tools Appl 81(8):10743–10776. https://doi.org/10.1007/s11042-022-12242-2

5. Besiru JM, Kehinde AM, Martin AO, Ayodeji OS (2020) Diagnosis of diabetes mellitus type II using a feed forward back propagation neural network. J Comput Sci Control Syst 13(1):39–43

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