Open Access
·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667
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The Journal of Information and Optimization Sciences (JIOS) is a world leading journal publishing high quality, rigorously peer-reviewed original research in all mathematically-oriented theoretical and applied topics in information sciences, optimization sciences and related areas since 1980. Subjects include but are not limited to:
• Information Sciences
• Optimization Sciences
• Control Theory
• Operational Research
• Decision Sciences
• Information Theory
• Information Technology
• Computer Networks and Communications
• Mathematical Programming
• Modelling and Simulation
• Database Management
• Applications to Engineering Sciences
• Applications to Technology
Issues up to 2022 co-published with and available at:
The development of healthcare systems has been greatly enhanced by recent advances in the IoT and AI, especially machine learning technology, which will now be used to prevent, diagnose and treat patients they have been monitored remotely and in the comfort of your home so This study focuses more on in-depth learning about building remote health care systems for diagnosing diabetes. Both the speed of data processing and the accuracy of detection are enhanced in the proposed system. The two steps in the hybrid deep learning approach (NCA-CNN) method present are as follows: First, significant features are selected from all data, then selected features are classified in NCA algorithm is a statistical method that selects important features and scores features based on data analysis findings. Subsequently, the variable depth of tissue classifies the most dramatic features, leading to more accurate diagnosis. The evaluation results show that the accuracy of the proposed method is 96.88%.
[1] A. K. Saini, M. L. Saini, D. K. Srivastava, S. Singh, P. Vats, and T. K. Tak, “Secure communication framework using lattice-based encryption and image steganography,” Journal of Discrete Mathematical Sciences and Cryptography, vol. 28, no. 5-B, pp. 1855–1864 (2025).[2] B. Shilpa, P. R. Kumar, and R. K. Jha, “LoRa DL: A deep learning model for enhancing the data transmission over LoRa using autoencoder,” The Journal of Supercomputing, vol. 79, no. 15, pp. 17079-17097 (2023).[3] V. Sendilraj, A. Bhasin, S. K. Bhadada, and M. Bhasin, “DFUCare: Automated robust diabetic foot ulcer monitoring platform Deep learning platform for diabetic foot ulcer detection, analysis, and monitoring,” Frontiers in Endocrinology, vol. 15, no. 1386613 (2024).[4] Sonam and Jyoti, “An Apriori algorithm-based framework for measuring and improving transactional dataset efficiency,” Journal of Statistics and Management Systems, vol. 28, no. 6, pp. 1179–1189 (2025).[5] N. Arivazhagan, K. Somasundaram, D. Vijendra Babu, M. Gomathy Nayagam, R. M. Bommi, G. B. Mohammad, ... and V. Prabhu Sundramurthy, “Cloud-Internet of Health Things (IoHT) task scheduling using hybrid moth flame optimization with deep neural network algorithm for E-healthcare systems,” Scientific Programming, vol. 2022, no. 1, Art. no. 4100352 (2022).[6] T. He and N. Lia, “Age-structured model with varied contact patterns and vaccination of COVID-19 in Liaoning Province, China,” Journal of Statistics and Management Systems, vol. 27, no. 8, pp. 1525–1539 (2024).[7] P. R. Kumar, B. Shilpa, and R. K. Jha, “BrainTract: segmentation of white matter fiber tractography and analysis of structural connectivity using hybrid convolutional neural network,” Neuroscience, vol. 580, pp. 218–230 (2025).[8] R. Ranjan, D. Pandey, A. K. Rai, D. Gupta, P. Singh, P. R. Kumar, and S. N. Mohanty, “A manifold-level hybrid deep learning approach for sentiment classification using an autoregressive model,” Applied Sciences, vol. 13, no. 5, p. 3091 (2023).[9] K. Kavita, R. Kulkarni, A. H. Prasad, B. Jeyakumar, M. Thaile, and S. Gore, “A novel optimization-based blockchain technology using health care data for enhancing security and privacy in the medical system,” Journal of Discrete Mathematical Sciences and Cryptography, vol. 27, no. 8, pp. 2483–2494 (2024).[10] P. R. Kumar and B. Shilpa, “An IoT-based smart healthcare system with edge intelligence computing,” in Reconnoitering the Landscape of Edge Intelligence in Healthcare, Apple Academic Press, pp. 31-46 (2024).
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