Objective To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced ...

However, NGD faces several challenges associated with gamma-ray generation and attenuation complexities. Unlike GGD, which utilizes 0.662 MeV monoenergetic γ rays from a 137 Cs source, NGD employs ...

The Perspective by Tiwary et al. (8) offers a comprehensive overview of generative AI methods in computational chemistry. Approaches that generate new outputs (e.g., inferring phase transitions) by ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. This study used machine learning models to investigate the potential of biosorbents ...

LCGC International interviewed Bob Pirok from the University of Amsterdam, Netherlands to discuss strategies for enhancing method robustness in 2D LC, practical approaches for tracking peaks across ...

High-precision GNSS applications, such as real-time displacement monitoring and vehicle navigation, rely heavily on resolving carrier-phase ambiguities. However, traditional methods like the R-ratio ...

Background: Budd-Chiari syndrome (BCS) is a rare global condition with high recurrence rates. Existing prognostic scoring models demonstrate limited predictive efficacy for BCS recurrence. This study ...

1 Mathematics and Statistics, Austin Peay State University Clarksville, Tennessee, USA. 2 Technology, University of Central Missouri, Warrensburg, MO, USA. 3 Business ...

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft Your email has been sent A new “periodic table for machine learning” is reshaping how researchers explore AI, ...

Abstract: Quantum-enhanced machine learning is a rapidly evolving field that aims to leverage the unique properties of quantum mechanics to enhance classical machine learning. However, the practical ...