Background Although chest X-rays (CXRs) are widely used, diagnosing mitral stenosis (MS) based solely on CXR findings remains ...

In this video, we will look at the details of the RNN Model. We will see the mathematical equations for the RNN model, and ...

Organoid Intelligence (OI) represents a groundbreaking convergence of biology and technology, aiming to redefine biocomputing using brain organoids—three-dimensional neural structures derived from ...

This study presents a valuable advance in reconstructing naturalistic speech from intracranial ECoG data using a dual-pathway model. The evidence supporting the claims of the authors is solid, ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...

Learn what CNN is in deep learning, how they work, and why they power modern image recognition AI and computer vision programs.

Graph Neural Networks (GNNs) have become a powerful tool in order to learn from graph-structured data. Their ability to capture complex relationships and dependencies within graph structures, allows ...

Abstract: Deep learning is a powerful technique for data-driven learning in the era of Big Data. However, most deep learning models are deterministic models that ignore the uncertainty of data. Fuzzy ...