Nanopore signals and machine learning unlock new molecular analysis tool

Understanding molecular diversity is fundamental to biomedical research and diagnostics, but existing analytical tools ...
Tech Xplore on MSN

Microgrippers successfully developed to handle sub-millimeter-sized, complex objects

Miniaturized electronics and intricate objects require a certain finesse. Researchers have looked into the development of a ...
ascopubs.org

Machine learning–based classification of cancer types using genomic profiling data from the Australian Molecular Screening and Therapeutics (MoST) program.

Early detection of lung cancer in smokers using miRNA profiles and a hybrid deep learning framework. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not ...
Tech Xplore on MSN

VFF-Net algorithm provides promising alternative to backpropagation for AI training

Deep neural networks (DNNs), which power modern artificial intelligence (AI) models, are machine learning systems that learn ...
Iowa State University News Service

From a vision of AI in plant science to the reality of Pest-ID in global agriculture

Well, nine years later, artificial intelligence in agriculture isn’t just for the scientists. A tool developed by the four ...
insideHPC

Ask a Data Scientist: Unsupervised Learning

Ask a Data Scientist.” Once a week you’ll see reader submitted questions of varying levels of technical detail answered by a practicing data scientist – sometimes by me and other times by an Intel ...
Semiconductor Engineering

Using AI For Fault Detection And Classification In Manufacturing

Classic fault detection and classification has some classic problems. It’s reactive, time-consuming to set up, and any product change involves significant man-hours. Even then, it still misses a lot ...
National Academies

Making Machine Learning Safer in High-Stakes Settings

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, ...