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 patients with undiagnosed Alzheimer's disease, addressing a critical gap in ...
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 ...
techxplore

New training method helps AI models handle messy, varied medical image data

Hospitals do not always have the opportunity to collect data in tidy, uniform batches. A clinic may have a handful of carefully labeled images from one scanner while holding thousands of unlabeled ...
GitHub

RajaMuhammadAwais/Forensic-Media-Detection

The Forensic Media Detection (FMD) Tool is a comprehensive AI & ML-driven system designed to detect deepfake artifacts across multiple media modalities. The tool employs state-of-the-art deep learning ...
GitHub

autoencoder-anomaly-detection

This repo contains all my Deep Learning semester work, including implementations of FNNs, CNNs, autoencoders, CBOW, and transfer learning. I explored TensorFlow, Keras, PyTorch, and Theano while ...