AIMC Topic: Models, Statistical

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Statistical and machine learning models for predicting university dropout and scholarship impact.

PloS one
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 ...

MRI super-resolution reconstruction using efficient diffusion probabilistic model with residual shifting.

Physics in medicine and biology
Magnetic resonance imaging (MRI) is essential in clinical and research contexts, providing exceptional soft-tissue contrast. However, prolonged acquisition times often lead to patient discomfort and motion artifacts. Diffusion-based deep learning sup...

A comparative study of various statistical and machine learning models for predicting restaurant demand in Bangladesh.

PloS one
Precise demand forecasting has become crucial for merchants due to the growing complexity of client behavior and market dynamics. This allows them to enhance inventory management, minimize instances of stock outs, and enhance overall operational effi...

Enhancing particulate matter prediction in Delhi: insights from statistical and machine learning models.

Environmental monitoring and assessment
This study advances our approach to modeling particulate matter levels-specifically, PM and PM-in Delhi's dynamic urban environment through an extensive evaluation of traditional time series models (ARIMAX, SARIMAX) and machine learning models (RF, S...

Forecasting malaria cases using climate variability in Sierra Leone.

Malaria journal
BACKGROUND: Malaria continues to pose a public health challenge in Sierra Leone, where timely and accurate forecasting can guide more effective interventions. Although seasonal models such as Seasonal Autoregressive Integrated Moving Average (SARIMA)...

Systemic inflammation mediates the relationship between urinary cadmium and chronic cough risk: findings based on multiple statistical models.

Biometals : an international journal on the role of metal ions in biology, biochemistry, and medicine
Epidemiological research examining the relationship between urinary cadmium and the risk of chronic cough remains scarce. This study included 2965 participants for a cross-sectional study from the NHANES. The weighted quantile sum (WQS) regression, b...

Probabilistic design space exploration and optimization via bayesian approach for a fluid bed drying process.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
The concept of Design Space (DS), delineated as a region of investigated variables aimed at maintaining product quality, was introduced in the International Conference on Harmonisation (ICH) Q8 as a framework to direct pharmaceutical development. How...

Statistical algorithms for the analysis of deleterious genetic mutations.

Bio Systems
We present algorithms for model selection and parameter estimation concerning deleterious genetic mutations. Three models are considered: single gene mutation, double cross-effect mutations or no genetic cause. Each of these models include unknown pa...

A comparison of statistical methods for deriving occupancy estimates from machine learning outputs.

Scientific reports
The combination of autonomous recording units (ARUs) and machine learning enables scalable biodiversity monitoring. These data are often analysed using occupancy models, yet methods for integrating machine learning outputs with these models are rarel...

An investigation into the impact of temporality on COVID-19 infection and mortality predictions: new perspective based on Shapley Values.

BMC medical research methodology
INTRODUCTION: Machine learning models have been employed to predict COVID-19 infections and mortality, but many models were built on training and testing sets from different periods. The purpose of this study is to investigate the impact of temporali...