Unlocking data sets by calibrating populations of models to data density: A study in atrial electrophysiology | Zendy

Brodie Lawson | Zendy; Christopher Drovandi | Zendy; Nicole Cusimano | Zendy; Pamela Burrage | Zendy; Blanca Rodríguez | Zendy; Kevin Burrage | Zendy

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Unlocking data sets by calibrating populations of models to data density: A study in atrial electrophysiology

Author(s) -

Brodie Lawson,

Christopher Drovandi,

Nicole Cusimano,

Pamela Burrage,

Blanca Rodríguez,

Kevin Burrage

Publication year - 2018

Publication title -

science advances

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 5.928

H-Index - 146

ISSN - 2375-2548

DOI - 10.1126/sciadv.1701676

Subject(s) - calibration , data set , atrial action potential , set (abstract data type) , experimental data , computer science , population , identification (biology) , cardiac electrophysiology , data mining , statistics , artificial intelligence , electrophysiology , mathematics , medicine , biology , botany , environmental health , repolarization , programming language

We describe a statistically informed calibration of in silico populations to explore variability in complex systems.

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