#deep-learning

#deep-learning

The alarming findings were published in the journal Cell Reports Medicine, showing that four leading AI-enhanced pathology diagnostic systems differ in accuracy depending on patients ' age, gender, and race - demographic data, disturbingly, that the AI is extracting directly from pathology slides, a feat that's impossible for human doctors. To conduct the study, researchers at Harvard University combed through nearly 29,000 cancer pathology images from some 14,400 cancer patients. Their analysis found that the deep learning models exhibited alarming biases 29.3 percent of the time - on nearly a third of all the diagnostic tasks they were assigned, in other words.

Chronic stress that persists over an extended period of time can lead to a higher risk of developing physical and mental health issues. Having a method to quantify stress levels can be a useful diagnostic tool for clinicians. Researchers at Johns Hopkins University School of Medicine have developed a new, noninvasive, artificial intelligence (AI) deep learning digital biomarker for chronic stress, which was unveiled at the recent annual meeting of the Radiological Society of North America (RSNA).

British startup Wayve has begun testing self-driving cars with Nissan in Japan ahead of a 2027 launch to consumers, as the company said it was in talks for a $500m investment from the chip-maker Nvidia. Wayve, based in London, said it had installed its self-driving technology on Nissan's electric Ariya vehicles and tested them on Tokyo's streets, after first agreeing a deal with the Japanese carmaker in April.

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.