RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.
A Cornell University fellow develops strategies to extract more than correlations from algorithms’ predictions.
Abstract: Advances in artificial intelligence (AI) and machine learning (ML) have significantly enhanced fire risk assessment by enabling predictive analytics, real-time decision support, and ...
BrainIAC, a breakthrough AI foundation model, is able to predict brain age, dementia, time-to-stroke, and brain cancer from brain magnetic resonance imaging (MRI).
Medical researchers at Mass General Brigham say the self-supervised foundational model can identify inherent features from ...
A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
Abstract: Analyzing the temperature evolution during the construction of mass concrete and establishing accurate prediction models are essential for ensuring structural quality and construction safety ...
After apparently promising a climb back to $100,000 for about a week, Bitcoin (BTC) suddenly reversed late on Sunday, January 18, and ended up trading at $93,013 by press time on Monday. BTC price ...
Production-ready machine learning system that predicts bike rental demand using real-world public APIs and historical data. Built with Docker-first architecture for seamless deployment, the system ...
Objective: To construct a prediction model for teicoplanin (TEIC) plasma concentrations through machine learning and deep learning techniques in patients with liver disease using real-world clinical ...
Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...
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