A curated, citation-backed cardiac channel-block dataset and human ventricular action-potential simulation pipeline that quantifies how input data variability propagates into proarrhythmia risk distributions and classification stability, rather than issuing rigid safety verdicts.
python json-schema computational-biology open-science monte-carlo-simulation uncertainty-quantification sbml data-curation action-potential cellml cipa in-silico cardiac-electrophysiology quantitative-pharmacology myokit qt-prolongation proarrhythmia torsade-de-pointes safety-pharmacolog channel-blockers
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Updated
Jun 10, 2026 - Python