Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
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 ...
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 ...
Objectives: The associations between various minerals' intake and thyroid dysfunction (TD), including hyperthyroidism and hypothyroidism, are still inconclusive, which may be attributed to the ...
1 Mathematics and Statistics, Austin Peay State University Clarksville, Tennessee, USA. 2 Technology, University of Central Missouri, Warrensburg, MO, USA. 3 Business ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results