AI tool can detect missed Alzheimer's diagnoses while reducing disparities

Researchers at UCLA have developed an artificial intelligence tool that can use electronic health records to identify ...
Becker's Hospital Review

UCLA Health develops AI to detect undiagnosed Alzheimer’s cases

UCLA Health develops AI to detect Alzheimer's cases using EHR data, improving early identification across diverse ...
IEEE

Machine Learning-Based Anomaly Detection of Correlated Sensor Data: An Integrated Principal Component Analysis-Autoencoder Approach

Abstract: This research proposes a lightweight hybrid approach for anomaly detection in correlated IoT sensor data, combining PCA for fast monitoring and Autoencoders for deeper analysis. Validated on ...
IEEE

Autoencoder-based Temporal Convolutional Network for Real-Time Anomaly Detection in Large-Scale Network Traffic

Abstract: Nowadays, the rapid growth of network traffic has needed the development of efficient anomaly detection systems to ensure network security and reliability. However, the existing One-Class ...