#deep-learning

#deep-learning

Neural networks are some of the most promising artificial intelligence (AI) models. These systems process data similarly to the human brain, passing information through a complex network of nodes in the same way information goes through layers of neurons. That makes them capable of solving complicated problems in minimal time, which is particularly advantageous in the medical industry. Drug discovery is a vital but challenging process.

Whole slide images (WSIs) can be too large to be processed directly by Deep Learning models due to their sizes, often exceeding 6 GB of memory.

Traditional keyword matching in information retrieval fails to understand user intent, which leads to irrelevant results and limits the diversity of responses, requiring query alterations to be effective.

Recent advancements suggest that employing small Graph Neural Networks to craft preconditioners could significantly enhance performance while preserving necessary sparsity, thereby optimizing computational efficacy.

The proposed framework exhibits super-balanced performance and efficiency, but has limitations such as the computational cost of the visual backbone and restricted training data.

Glean is an AI-powered enterprise search and knowledge management platform that helps employees quickly find the information they need, no matter where it's stored.