Search results (67)
« Back to PublicationsPeruanos en Harvard: cómo se ve (y piensa) el Perú desde una de las mejores universidades del mundo
Internet publication
Arce Ruiz M., (2026)
Hierarchical X-ray microscopy and mesoscopic diffusion MRI in the same brain reveal the human connectome across scales
Preprint
Chourrout M. et al, (2026)
Metrics for Artificial Intelligence in Medicine: A Reference Resource.
Journal article
Gonzales RA. et al, (2026), Radiol Artif Intell
Roadmap: An Ontology of Medical AI Models and Datasets.
Journal article
Suri A. et al, (2026), Radiol Artif Intell
mated extraction of artificial intelligence model and dataset characteristics from papers to promote transparency
Conference paper
Suri A. et al, (2026)
SCMR 2026 in Brazil: Developing generalist AI methods for cardiovascular magnetic resonance and strengthening regional collaboration in Latin America
Internet publication
Gonzales RA., (2026)
Differentiating ischemic from healthy myocardium using cardiovascular magnetic resonance dipyridamole rest and stress T1 mapping.
Journal article
Chang Y-T. et al, (2026), Sci Rep, 16
From first lines of code to peer-reviewed science: what high schoolers can build with AI research
Internet publication
Gonzales RA., (2026)
Feasibility of MRI-based assessment of pulmonary vein flow and isovolumic relaxation time for diastolic dysfunction
Conference paper
Barrientos L. et al, (2026)
microstructure-informed common coordinate framework for the macaque brain
Conference paper
Gonzales RA. et al, (2026)
Differentiating ischemic from healthy myocardium using cardiovascular magnetic resonance dipyridamole rest and stress T1 mapping
Conference paper
Chang YT. et al, (2026)
Highlights of the Society for Cardiovascular Magnetic Resonance 2025 conference: Leading the way to accessible, efficient, and sustainable cardiovascular magnetic resonance.
Journal article
Prieto C. et al, (2025), Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance, 27
mated, efficient extraction of structured metadata for radiology AI models and datasets
Conference paper
Suri A. et al, (2025)
Generalist deep learning for cross-modality landmark annotation in cardiovascular magnetic resonance
Conference paper
Gonzales RA. et al, (2025)