A machine learning-based approach for RF transfer function modeling of active implantable medical electrodes at 3T MRI.

Provide an efficient alternative of transfer function modeling, which allows a more realistic tissue distribution and the potential underestimation of in vivo RF-induced power deposition near the AIM electrode can be reduced.&#xD.