Head and neck cancer (HNC) is one of the most common malignancies worldwide, with high morbidity and mortality rates.

Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...

The project titled "Medical Image Classification for Disease Diagnosis Using Convolutional Neural Networks" aims to develop a robust and accurate machine learning model for the automatic ...

Breakthrough AI foundation model called BrainIAC is able to predict brain age, dementia, time-to-stroke, and brain cancer ...

Medical researchers at Mass General Brigham say the self-supervised foundational model can identify inherent features from ...

Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Abstract: We introduce LCMatch, a novel semi-supervised scene classification framework designed to enhance the performance of remote sensing image classification. Our method improves upon the existing ...

Abstract: Federated learning is an emerging privacy-preserving distributed learning paradigm, in which many clients collaboratively train a shared global model under the orchestration of a remote ...