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) and predicts the background field; the local tissue field is total − background, masked. The authors' trained MATLAB network was exported to ONNX and is run here with ONNX Runtime — no MATLAB Runtime — reproducing the MATLAB output to ~1e-8 at a fraction of the memory and image size. QSM-CI reconstruction method bfrnet. Browse and run it at https://qsmxt.github.io/QSM-CI/submission.html?method=bfrnet.
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 provides the complete code, frozen configurations, calibration and test seeds, raw episode- and step-level logs, processed tables, statistical outputs, figures, environment manifests, checksums, and a self-contained Google Colab workflow for a reviewer-requested compa…
Initial public release This is the first public software release accompanying the manuscript: A Theory-Grounded Diagnostic Framework for Temporal Computation in Spiking Neural Networks The framework separates four properties that are often conflated in the analysis of spiking neu…
Early warning of a training-time collapse has so far been read from a model’s internals. This paper shows the same precursor is legible in the model’s own output distribution: per-token entropy variance and lag-1 autocorrelation, computed from the log-probabilities any inference…
Background. Post-marketing pharmacovigilance depends on the timely identification of serious individual case safety reports (ICSRs) from large spontaneous-reporting databases such as the FDA Adverse Event Reporting System (FAERS). Machine-learning triage has been proposed to prio…
Background: Extended length of stay (eLOS) after geriatric hip fracture surgery strains scarce orthopaedic resources and inflates cost under diagnosis-related-group and diagnosis-intervention-packet reimbursement schemes. Machine-learning predictors of eLOS exist but frequently c…