A new study published in Genome Research presents an interpretable artificial intelligence framework that improves both the accuracy and transparency of genomic prediction, a key challenge in fields ...
Researchers at Stevens Institute of Technology used machine learning tools and social network theory—the study of how people ...
14d
A machine learning model may enable liver cancer risk prediction with routine clinical information
A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results ...
8don MSN
Ultra‑robust machine‑learning models run stable molecular simulations at extreme temperatures
Researchers at The University of Manchester have created a physics‑informed machine‑learning model that can run molecular ...
Que.com on MSN
The next frontier of machine learning: 2026 breakthroughs and the rise of world models
The Next Frontier of Machine Learning: 2026 Breakthroughs and the Rise of World Models The landscape of artificial intelligence and ...
Recent advances in machine learning have opened transformative avenues for investigating complex problems in string theory and geometry. By integrating sophisticated algorithms with theoretical ...
David J. Silvester, a mathematics professor at the University of Manchester, has developed a novel machine-learning method to ...
Bacterial immune systems protect against viral invaders called phages by precisely targeting specific phage genetic sequences ...
A machine learning model using routine clinical data more accurately predicted 5-year heart failure risk in patients with CKD ...
Using routine clinical data, the model gauges liver cancer risk better than existing tools, offering a potential way to identify high-risk patients missed by current screening criteria.
Some results have been hidden because they may be inaccessible to you
Show inaccessible results