A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
New AI model decodes brain signals captured noninvasively via EEG opens the possibility of developing future neuroprosthetics ...
AMD requires a Senior AI/ML and GPU Performance QA Engineer who will manage validation and performance testing for machine ...
Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
Musculoskeletal (MSK) conditions drive a large share of global pain, disability, and lost productivity. Rehabilitation can be effective, but outcomes vary ...
A signal-processing–based framework converts DNA sequences into numerical signals to identify protein-coding regions. By integrating spectral analysis and SVM classification, the approach improves ...
AI-native air interfaces represent a shift from mathematical models to learned representations at the PHY layer.
In a study titled Recent Applications of Machine Learning Algorithms for Pesticide Analysis in Food Samples, published in the ...
Edge AI addresses high-performance, low-latency requirements by embedding intelligence directly into industrial devices.
Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...
AI: How does this technological revolution fit with the pharmaceutical regulators who oversee the pharmaceutical sector at ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results