Computational intelligence and neuroscience
35978897
Artificial neural network (ANN) techniques are widely used to screen the data and predict the experimental result in pharmaceutical studies. In this study, a novel dissolution result prediction and screen system with a backpropagation network and reg...
Journal of environmental sciences (China)
35459476
Atmospheric particulate matter pollution has attracted much wider attention globally. In recent years, the development of atmospheric particle collection techniques has put forwards new demands on the real-time source apportionments techniques. Such ...
Computational and mathematical methods in medicine
35419074
In the current information and technology era, business enterprises are focusing in performing the process effectively by reducing the waiting time in completing the work, reduce latency and deploy the resources effectively so as to service the patie...
OBJECTIVE: We aimed to identify existing hypertension risk prediction models developed using traditional regression-based or machine learning approaches and compare their predictive performance.
Machine learning models may outperform traditional statistical regression algorithms for predicting clinical outcomes. Proper validation of building such models and tuning their underlying algorithms is necessary to avoid over-fitting and poor genera...
Several recently developed methods have the potential to harness machine learning in the pursuit of target quantities inspired by causal inference, including inverse weighting, doubly robust estimating equations and substitution estimators like targe...
MOTIVATION: Mass spectrometry-based untargeted lipidomics aims to globally characterize the lipids and lipid-like molecules in biological systems. Ion mobility increases coverage and confidence by offering an additional dimension of separation and a ...
Proceedings of the National Academy of Sciences of the United States of America
35969737
Testing the significance of predictors in a regression model is one of the most important topics in statistics. This problem is especially difficult without any parametric assumptions on the data. This paper aims to test the null hypothesis that give...
Analysis of data with a censored survival response and high-dimensional omics measurements is now common. Most of the existing analyses are based on specific (semi)parametric models, in particular the Cox model. Such analyses may be limited by not ha...
Soil organic matter (SOM) is an important source of nutrients required during crop growth and is an important component of cultivated soil. In this paper, we studied the possibility of using deep learning methods to establish a multi-feature model to...