AIMC Topic: Models, Statistical

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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...

Multi-Granularity Autoformer for long-term deterministic and probabilistic power load forecasting.

Neural networks : the official journal of the International Neural Network Society
Long-term power load forecasting is critical for power system planning but is constrained by intricate temporal patterns. Transformer-based models emphasize modeling long- and short-term dependencies yet encounter limitations from complexity and para...

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...

Integrating AI for infectious disease prediction: A hybrid ANN-XGBoost model for leishmaniasis in Pakistan.

Acta tropica
Addressing leishmaniasis infection remains a substantial challenge in KP-Pakistan due to the increased infection prevalence. Understanding its spreading tool offerings is a major challenge. We essentially design effective approaches to pinpoint its e...

A Neural Network Model for Intelligent Classification of Distal Radius Fractures Using Statistical Shape Model Extraction Features.

Orthopaedic surgery
OBJECTIVE: Distal radius fractures account for 12%-17% of all fractures, with accurate classification being crucial for proper treatment planning. Studies have shown that in emergency settings, the misdiagnosis rate of hand/wrist fractures can reach ...

An ensemble approach improves the prediction of the COVID-19 pandemic in South Korea.

Journal of global health
BACKGROUND: Modelling can contribute to disease prevention and control strategies. Accurate predictions of future cases and mortality rates were essential for establishing appropriate policies during the COVID-19 pandemic. However, no single model yi...

An Interpretable Model With Probabilistic Integrated Scoring for Mental Health Treatment Prediction: Design Study.

JMIR medical informatics
BACKGROUND: Machine learning (ML) systems in health care have the potential to enhance decision-making but often fail to address critical issues such as prediction explainability, confidence, and robustness in a context-based and easily interpretable...

Current experimental, statistical, and mechanistic approaches to optimizing biomolecule separations in aqueous two-phase systems.

Journal of chromatography. A
Aqueous two-phase systems (ATPS) have been used to purify a range of biomolecules, including small molecules, monoclonal antibodies, viruses, and whole cells. They are known for selective separations, creating a stabilizing, low-shear environment, an...