Publications by authors named "R Balamanigandan"

Article Synopsis
  • - The integration of IoT and cloud services enhances healthcare communication and quality of life by utilizing predictive analytics powered by AI and deep learning for proactive disease management.
  • - A new approach, termed IOT-CC-DD-OICAN-SHS, uses IoT devices to gather health data on conditions like diabetes and heart disease, processing this data in the cloud for accurate disease classification via an Improved Generative Adversarial Network (IGAN).
  • - The IGAN is optimized using the Flamingo Search optimization algorithm and shows improved performance metrics, achieving higher accuracy and faster execution times compared to existing healthcare methodologies.
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Stroke prediction has become one of the significant research areas due to the increasing fatality rate. Hence, this article proposes a novel Adaptive Weight Bi-Directional Long Short-Term Memory (AWBi-LSTM) classifier model for stroke risk level prediction for IoT data. To efficiently train the classifier, Hybrid Genetic removes the missing data with Kmeans Algorithm (HKGA), and the data are aggregated.

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The integration of virtual reality (VR), augmented reality (AR), and mixed reality (MR) in urological practices and medical education has led to modern training systems that are cost-effective and with an increased expectation toward surgical performance and outcomes. VR aids the user in interacting with the virtual environment realistically by providing a three-dimensional (3D) view of the structures inside the body with high-level precision. AR enhances the real environment around users by integrating experience with virtual information over physical models and objects, which in turn has improved understanding of physiological mechanisms and anatomical structures.

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