Machine learning and other modeling approaches could aid in forecasting the arrival of floating Sargassum rafts that clog ...
Energy use in healthcare is a growing policy concern. Hospitals account for a significant share of public sector emissions, ...
ABSTRACT: This paper proposes a hybrid AI framework that integrates technical indicators, fundamental data, and financial news sentiment into a stacked ensemble learning model. The ensemble combines ...
Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...
An ocean-mining company has funded some of the most comprehensive scientific studies of the deep seabed to date, and peer-reviewed results have begun to emerge. A collage of foraminifera, a kind of ...
The electrocardiogram (ECG) is an important tool for exploring the structure and function of the heart due to its low cost, ease of use, efficiency, and non-invasive nature. With the rapid development ...
Deep learning has emerged as a transformative tool for the automated detection and classification of seizure events from intracranial EEG (iEEG) recordings. In this review, we synthesize recent ...
Imagine a town with two widget merchants. Customers prefer cheaper widgets, so the merchants must compete to set the lowest price. Unhappy with their meager profits, they meet one night in a ...
This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...
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