Tuberculosis (TB) caused by the bacteria Mycobacterium tuberculosis (M. tb), continues to pose a significant worldwide health threat. The advent of drug-resistant strains of the disease highlights the critical need for novel treatments. The unique ce...
INTRODUCTION: Continuous renal replacement therapy (CRRT) is a prolonged continuous extracorporeal blood purification therapy to replace impaired renal function. Typically, CRRT therapy requires routine anticoagulation, but for patients at risk of bl...
This research examines the seismic hazard impact on railway infrastructure along the U.S. West Coast (Washington, Oregon and California), using machine learning to explore how measures of seismic hazard such as fault density, earthquake frequency, an...
Credit scorecards are essential tools for banks to assess the creditworthiness of loan applicants. While advanced machine learning models like XGBoost and random forest often outperform traditional logistic regression in predictive accuracy, their la...
Due to the diverse controlling factors and their uneven spatial distribution, especially atmospheric deposition from smelters, assessing and predicting the accumulation of heavy metals (HM) in crops across smelting-affected areas becomes challenging....
In the field of microplastics (MPs) toxicity prediction, machine learning (ML) computer simulation techniques are showing great potential. In this study, six ML algorithms were utilized to predict the toxicity of MPs on BEAS-2B cells based on quantit...
International journal of pharmaceutics
Aug 11, 2024
The pharmaceutical industry is increasingly drawn to the research of innovative drug delivery systems through the use of supercritical CO (scCO)-based techniques. Measuring the solubility of drugs in scCO at varying conditions is a crucial parameter ...
: Polycystic ovary syndrome (PCOS) is a complex disorder that can negatively impact the obstetrical outcomes. The aim of this study was to determine the predictive performance of four machine learning (ML)-based algorithms for the prediction of adver...
In the context of early disease detection, machine learning (ML) has emerged as a vital tool. Feature selection (FS) algorithms play a crucial role in ensuring the accuracy of predictive models by identifying the most influential variables. This stud...
Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
Aug 10, 2024
PURPOSE: To develop a machine-learning model to predict clinical outcomes after medial patellofemoral ligament reconstruction (MPFLR) and identify the important predictive indicators.
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