Biochemical and biophysical research communications
Aug 6, 2025
Chimeric antigen receptor T (CAR-T)-cell therapy has emerged as a promising treatment for hematologic malignancies. Accurate monitoring of CAR expression levels is essential for optimizing therapeutic efficacy and ensuring patient safety. Conventiona...
Machine learning (ML) has significantly transformed biomedical research, leading to a growing interest in model development to advance classification accuracy in various clinical applications. However, this progress raises essential questions regardi...
BACKGROUND: Cardiovascular disease (CVD) is the leading cause of mortality and morbidity in China and worldwide while we are lacking in validated primary prevention model specifically for Chinese. To identify CVD high-risk individuals for early inter...
Raman spectroscopy has attracted significant attention in various biochemical detection fields, especially in the rapid identification of pathogenic bacteria. The integration of this technology with deep learning to facilitate automated bacterial Ram...
INTRODUCTION: Accurate breast cancer risk prediction is essential for early detection and personalized prevention strategies. While traditional models, such as Gail and Tyrer-Cuzick, are widely utilized, machine learning-based approaches may offer en...
Coagulation is one of the most crucial steps in a Drinking Water Treatment Plant (DWTP). The coagulant dose required for the removal of particles and natural organic matter (NOM) is typically determined through jar tests. However, this method is time...
BACKGROUND: Individualized prediction of health outcomes supports clinical medicine and decision making. Our primary objective was to offer a comprehensive survey of methods for the dynamic prediction of Alzheimer's disease (AD), encompassing both co...
In response to Oka et al.'s letter, we conducted additional statistical analyses to validate the robustness of our osteoporosis risk prediction model using NHANES 2007-2014 data (n = 7924). We evaluated 10 key predictors through Spearman's rho, Kenda...
This paper comments on the valuable contribution by Carvalho and Gavaia regarding machine learning for osteoporosis risk prediction, particularly their use of a stacking ensemble model and feature importance analysis. While acknowledging the model's ...
Although student dropout is an inevitable aspect of university enrollment, when analyzed, universities can gather information which enables them to take preventative actions that mitigate dropout risk. We study a data set consisting of 4,424 records ...
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