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Validation of Random Forest Machine Learning Models to Predict Dementia-Related Neuropsychiatric Symptoms in Real-World Data
(IOS Press, 2020)
Background: Neuropsychiatric symptoms (NPS) are the leading cause of the social burden of dementia but their role is underestimated.
Objective: The objective of the study was to validate predictive models to separately ...
Interpreting Remaining Useful Life estimations combining Explainable Artificial Intelligence and domain knowledge in industrial machinery
(IEEE, 2020)
This paper presents the implementation and explanations of a remaining life estimator model based on machine learning, applied to industrial data. Concretely, the model has been applied to a bushings testbed, where fatigue ...
Towards robust defect detection in casting using contrastive learning
(Springer, 2023)
Defect detection plays a vital role in ensuring product quality and safety within industrial casting processes. In these dynamic environments, the occasional emergence of new defects in the production line poses a significant ...
A Methodology for Advanced Manufacturing Defect Detection through Self-Supervised Learning on X-ray Images
(MDPI, 2024)
In industrial quality control, especially in the field of manufacturing defect detection, deep learning plays an increasingly critical role. However, the efficacy of these advanced models is often hindered by their need ...