Exponential Spider Wasp-Optimized Deep Learning Model for Type-2 Diabetes Detection Using Gene Expression Data

International Journal of Electronics and Communication Engineering
© 2025 by SSRG - IJECE Journal
Volume 12 Issue 6
Year of Publication : 2025
Authors : Chetan Nimba Aher, Madhavi Ranjeet Patil, Neha Ganvir, Sumati Manoj Jagdale
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How to Cite?

Chetan Nimba Aher, Madhavi Ranjeet Patil, Neha Ganvir, Sumati Manoj Jagdale, "Exponential Spider Wasp-Optimized Deep Learning Model for Type-2 Diabetes Detection Using Gene Expression Data," SSRG International Journal of Electronics and Communication Engineering, vol. 12,  no. 6, pp. 54-64, 2025. Crossref, https://doi.org/10.14445/23488549/IJECE-V12I6P105

Abstract:

Type-2 Diabetes Mellitus (T2DM) occurs by insulin dysfunction, a chronic disease. Moreover, the human body cannot react with high sugar due to low secretion of insulin, which increases the blood sugar level. Due to the resistance of insulin or its low production, T2DM patients suffer a lot. The existing diagnosis process faces challenges such as low reliance on testing data, limited accessibility and chances for misdiagnosis. A new model, Exponential Spider Wasp Optimization, is introduced to address these issues, enabling the Quantum Dilated Convolutional Neural Network (ESWO_QDCNN) to detect T2DM. Initially, gene expression data is considered input from the gene expression dataset. Afterwards, the data transformation process is performed using Box-Cox transformation. Next, the feature selection process is performed by employing weighted Euclidean distance. Lastly, T2DM detection is attained by utilizing QDCNN, which is tuned using Exponential Spider Wasp optimization (ESWO). Here, the hybrid approach ESWO is developed by utilizing Exponential Weight Moving Average (EWMA) and Spider Wasp Optimizer (SWO). In addition to this, ESWO_QDCNN has achieved 91.524% accuracy, 90.854% sensitivity and 92.290% specificity.

Keywords:

Gene Expression Data, Type2 Diabetes mellitus, Deep learning, Quantum Dilated Convolutional Neural Network, Spider Wasp Optimizer.

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