60 citations
- Universitat de ValènciaES3 papers
- Aix-Marseille UniversitéFR1 paper
- Amen ClinicsUS1 paper
- Amsterdam NeuroscienceNL1 paper
- Amsterdam University Medical CentersNL1 paper
- Australian e-Health Research CentreAU1 paper
- Azienda-Unita' Sanitaria Locale Di CesenaIT1 paper
- Barcelona Biomedical Research ParkES1 paper
- Barcelona Institute for Global HealthES1 paper
- Basque Center on Cognition, Brain and LanguageES1 paper
- Basque GovernmentES1 paper
- Berlin Institute of Health at Charité - Universitätsmedizin BerlinDE1 paper
6 papers
Overcoming Standardization: Revealing Hidden Age Patterns of Suicide with Spatiotemporal Models
J. Martín-Pozuelo, A. López-Quílez, X. Barber +1
Indirect standardization is widely used in disease mapping to control for confounding, but relies on restrictive assumptions that may bias estimates if violated. Using data on suic…
Characterisation of exposure to non-ionising electromagnetic fields in the Spanish INMA birth cohort: Study protocol
M. Gallastegi, M. Guxens, A. Jimenez-Zabala +15
Analysis of the association between exposure to electromagnetic fields of non-ionising radiation (EMF-NIR) and health in children and adolescents is hindered by the limited availab…
Ultra-high resolution multimodal MRI densely labelled holistic structural brain atlas
José V. Manjón, Sergio Morell-Ortega, Marina Ruiz-Perez +16
In this paper, we introduce a novel structural holistic Atlas (holiAtlas) of the human brain anatomy based on multimodal and high-resolution MRI that covers several anatomical leve…
The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)
Russell A. Poldrack, Christopher J. Markiewicz, Stefan Appelhoff +111
The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is mean…
Machine learning approaches for COVID-19 detection from chest X-ray imaging: A Systematic Review
Harold Brayan Arteaga-Arteaga, Melissa delaPava, Alejandro Mora-Rubio +12
There is a necessity to develop affordable, and reliable diagnostic tools, which allow containing the COVID-19 spreading. Machine Learning (ML) algorithms have been proposed to des…
Automatic Semantic Segmentation of the Lumbar Spine: Clinical Applicability in a Multi-parametric and Multi-centre Study on Magnetic Resonance Images
Jhon Jairo Saenz-Gamboa, Julio Domenech, Antonio Alonso-Manjarrés +2
One of the major difficulties in medical image segmentation is the high variability of these images, which is caused by their origin (multi-centre), the acquisition protocols (mult…