Achieving High Accuracy in Predicting the Probability of Periprosthetic Joint Infection From Synovial Fluid in Patients Undergoing Hip or Knee Arthroplasty: The Development and Validation of a Multivariable Machine Learning Algorithm.

Background and objective The current periprosthetic joint infection (PJI) diagnostic guidelines require clinicians to interpret and integrate multiple criteria into a complex scoring system. Also, PJI classifications are often inconclusive, failing to provide a clinical diagnosis. Machine learning (ML) models could be leveraged to reduce reliance on these complex systems and thereby reduce diagnostic uncertainty.

Measuring the 2D baryon acoustic oscillation signal of galaxies in WiggleZ: cosmological constraints.

We present results from the 2D anisotropic baryon acoustic oscillation (BAO) signal present in the final data set from the WiggleZ Dark Energy Survey. We analyse the WiggleZ data in two ways: first using the full shape of the 2D correlation function and secondly focusing only on the position of the BAO peak in the reconstructed data set. When fitting for the full shape of the 2D correlation function we use a multipole expansion to compare with theory.

Integrated Assessment of Neurodynamic and Vegetative Indicators in Adolescents: Age- and Gender-Related Differences and Typological Features.

We examined schoolchildren aged 11-16 years (n = 930) and determined the features of neurodynamic and vegetative parameters associated with age and sex and the factors affectingthe psycho-physiological statusof adolescents. An analysis of the relationship of studied parameters in adolescents with different types of autonomic regulation showed thatthe evaluation of functional constitution has prognostic significance since it is indicative of the adaptation potential.