Synthetic breast phantom data in BIfTI phantom data standard (https://github.com/mrx-org/bifti-phantoms.git) for MRI simulation using MR-zero. Phantom was presented and used for the simulations in the article "Breast Digital Twin: Towards simulation-guided acceleration of method development". It includes: multi-slice breast phantom for 3 T field strength: breast_3T.json multi-slice breast phantom for 7 T field strength: breast_7T.json single-slice breast phantom for 3 T field strength (with partial volume effects): breast_3T_single_slice_paper.json single-slice breast phantom for 7 T field strength (with partial volume effects): breast_7T_single_slice_paper.json
This paper presents an independent external assessment of OpenAI — the OpenAI Group PBC, the controlling OpenAI Foundation, and its publicly released GPT-series and o-series models — benchmarked against four governance frameworks: the EU AI Act (including its general-purpose AI a…
This dataset release represents Part 4 of the comprehensive young trefoil crop agricultural analysis project. While Part 1, Part 2 and Part 3 provided the raw image captures and camera parameters and machine-learning-ready image tiles. Part 4 delivers fully processed, georeferenc…
Deep-learning background field removal (BFRnet): a 3D dual-frequency octave-convolution U-net trained to predict the background field of the brain — including brains with significant pathological susceptibility sources (haemorrhage, calcification). Consumes the total field (ppm)…
INR-QSM — a subject-specific UNSUPERVISED deep-learning dipole inversion using an implicit neural representation. No pretrained weights: a sine-activated coordinate MLP (SIREN) is OPTIMIZED per-subject so that the susceptibility it represents, pushed through the QSM dipole forwar…
This record contains field-deployment datasets for two seabird species, streaked shearwaters and black-tailed gulls, used in the paper “Automated Ethogram Elaboration: A Cross-species Deep-learning Model Deployed On-board Enables Acceleration-triggered Capture of Diverse Behaviou…
While machine learning models achieve promising results in diabetes prediction, clinical adoption remains limited due to black-box nature and lack of stakeholder-specific communication. This study proposes a novel multi-level explanation framework that translates a single XGBoost…