The era of predictive modeling enhanced with machine learning and artificial intelligence (AI) to aid clinical ...

In addition, real-time anomaly detection poses high demands on low computational cost and model robustness, presenting substantial obstacles for unsupervised time-series anomaly detection.

This work investigates the use of autoencoders in deep learning for anomaly detection in the healthcare domain, with a focus on ethical and interpretable issues. The study creates a strong anomaly ...

Article citations More>> Mishra, P., Varadharajan, V., Tupakula, U. and Pilli, E.S. (2021) Unsupervised Anomaly Detection in IoT Using Autoencoders. IEEE Internet of Things Journal, 8, 9065-9078. has ...