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Early diagnosis of disorders based on behavioural shifts and biomedical signals
(Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2017)
There are many disorders that directly affect people’s behaviour. The people that are suffering from such a disorder are not aware of their situation, and too often the disorders are identified by relatives or co-workers ...
Aging effects on resting state networks after an emotional memory task
(Ediciones VISILAB, 2018)
Aging is one of the primary health concerns in nowadays world, being memory decline an important worry that affects daily functioning of healthy adults. This work presents a study of this kind of decline in normal aging, ...
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 ...
Aging Modulates the Resting Brain after a Memory Task: A Validation Study from Multivariate Models
(MDPI AG, 2019)
Recent work has demonstrated that aging modulates the resting brain. However, the study of these modulations after cognitive practice, resulting from a memory task, has been scarce. This work aims at examining age-related ...
Incorporation of Synthetic Data Generation Techniques within a Controlled Data Processing Workflow in the Health and Wellbeing Domain
(MDPI, 2022)
To date, the use of synthetic data generation techniques in the health and wellbeing domain has been mainly limited to research activities. Although several open source and commercial packages have been released, they have ...
Influencia de la frecuencia respiratoria inducida en los valores HRV
(Servicio Editorial de la Universidad del País VascoEuskal Herriko Unibertsitateko Argitalpen Zerbitzua, 2017)
The study of Place Cells, hippocampal neurons tuned to spatial locations in the environment, is central to elucidate how the brain encodes and retrieves spatial information. Advances in genetic and imaging technologies ...
Understanding human response to tactile stimuli: A Machine Learning approach
(VISLAB, 2018)
Whereas understanding human reaction to touch is of great interest in many medical applications, it is still a very unknown field. This research aims to clarify the nature of the relation between endogenous and exogenous ...
Synthetic Subject Generation with Coupled Coherent Time Series Data †
(MDPI, 2022)
A large amount of health and well-being data is collected daily, but little of it reaches its research potential because personal data privacy needs to be protected as an individual’s right, as reflected in the data ...
Synthetic Tabular Data Evaluation in the Health Domain Covering Resemblance, Utility, and Privacy Dimensions
(Thieme, 2023)
Background. Synthetic tabular data generation is a potentially valuable technology with great promise for data augmentation and privacy preservation. However, prior to adoption, an empirical assessment of generated synthetic ...
Comparative assessment of synthetic time series generation approaches in healthcare: leveraging patient metadata for accurate data synthesis
(Springer Nature, 2024)
Background
Synthetic data is an emerging approach for addressing legal and regulatory concerns in biomedical research that deals with personal and clinical data, whether as a single tool or through its combination with ...
