A team of UCSF researchers successfully tested several mainstream AI agents for the ability to analyze big data on women's ...
Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...
Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field ...
Background: Sepsis-induced coagulopathy (SIC) is a fatal complication in ICU patients, yet early risk prediction remains challenging. This study aimed to develop an interpretable machine learning ...
ABSTRACT: Background: Artificial intelligence (AI) technologies, including machine learning, natural language processing, and decision-support systems, are increasingly explored in primary care to ...
A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...
Abstract: The operational health of distribution transformers is critical for ensuring uninterrupted power delivery across smart grid infrastructures. This paper presents a predictive maintenance ...
Abstract: Predictive maintenance, utilising anomalous sound classification, demonstrates a strong potential to identify mechanical faults in industrial machinery. This research proposes a machine ...
This project aims to develop predictive maintenance models for e-mobility vehicles (e-bikes and e-scooters) using comprehensive datasets collected in real-world conditions around Dublin City ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results