In livestock, veterinary drug residues are detected through non-destructive methods like hyperspectral imaging. One case in ...

By using large bio-signal datasets, machine-learning algorithms are able to find clear relationships that apply to most people. To do this, we take a bio-signal and artificially create gaps of a ...

Unlike existing models that rely on expensive or infrequently collected data, BloomSense uses a cost-effective sensor ...

others with infections including COVID-19 or autoimmune diseases including lupus and Type 1 diabetes - the algorithm the researchers developed, called Mal-ID for machine learning for immunological ...

A research team has developed autonomous driving software that allows inexpensive sensors to detect transparent obstacles ...

Industries from retail to finance are using clustering to personalize services, detect fraud, monitor equipment and improve ...

Laser-based metal processing enables the automated and precise production of complex components, whether for the automotive industry or for medicine. However, conventional methods require time- and ...

SAVANA uses a machine learning algorithm to identify cancer-specific structural variations and copy number aberrations in long-read DNA sequencing data. The complex structure of cancer genomes means ...

However, in machine learning, computers use algorithms to analyze data ... machine learning is used for fraud detection, where algorithms analyze transaction patterns to detect anomalies that ...

(Jump to Section) TABLE OF CONTENTS Machine learning refers to the use of advanced mathematical models, or algorithms ... including sensors, databases, user interactions, and web scraping.