Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...

A noninvasive blood-based test identified cases of endometriosis that were missed by imaging, data at the Endocrine Society ...

Glucose-to-potassium ratio shows a J-shaped link with AKI after traumatic brain injury, with high levels predicting increased ...

A novel machine learning algorithm retrieves remote sensing reflectance (Rrs) from Himawari 8 geostationary data at 10 minute ...

The machine learning algorithm and subsequent simulations are fueled by data, expert knowledge and statistical models ...

Machine learning maps suggest that about 180 to 220 million people may rely on untreated groundwater with manganese above the ...

An artificial intelligence (AI) machine-learning model has been developed that can predict the risk of early death in trauma ...

Analyzing thousands of proteins from a single drop of blood is no longer science fiction. High-throughput proteomics has transformed biomarker discovery by enabling simultaneous profiling of thousands ...

Abstract: We introduce WildWood (WW), a new ensemble algorithm for supervised learning of Random Forest (RF) type. While standard RF algorithms use bootstrap out-of-bag samples to compute out-of-bag ...

Reports demonstrates that whole-brain Single Photon Emission Computed Tomography (SPECT) imaging, combined with advanced ...

Abstract: A printed circuit board (PCB) surface-mounted devices (SMDs) defect detection algorithm based on random forest (RF) was proposed to detect pin defects, resistor defects, and capacitor ...

Overview:  Explains how AI is transforming traditional microgrids into intelligent, self-optimizing energy systems.Compares ...