
Neural network learns when it should not be trusted
Researchers have developed a way for deep learning neural networks to rapidly estimate confidence levels in their output.
Researchers have developed a way for deep learning neural networks to rapidly estimate confidence levels in their output.
Digital phenotyping and machine learning have emerged as promising tools for monitoring patients with psychosis spectrum illnesses.
Scientists have used machine learning to predict the reemergence of existing infectious diseases.
A consortium is developing a mobile neurosensing system suitable for everyday use that detects epileptic seizures automatically.
Researchers developed an AI system that analyzes linguistic patterns to predict a youth’s risk for committing acts of school violence.
Currently, we are too focused on the topic of AI. In order, however, to leverage AI technology several challenges have to be mastered and a proper framework has to be established.
New machine learning study suggest the presence of at least nine gender “expressions”.
An artificial neural network can reveal patterns in huge amounts of gene expression data, and discover groups of disease-related genes.