also described.

\[sec:level1C\] Results
=======================

Table I shows the results from the driver search algorithm. The prediction success is consistently high both for the single circuit and two circuit scenarios. Additionally, the prediction is reached after a small number of electrogram recordings, typically around 5 –6. For comparison, the probability of recording an electrogram on the re-entrant circuit at any given point in the tissue is just under 2%.

        Target Driver        Prediction Probability    Mean Jumps
  ------------------------- ------------------------ ---------------
         One Circuit                 95.4%            5.0 $\pm$ 1.7
   Two Circuits, Circuit 1           94.8%            5.2 $\pm$ 2.3
   Two Circuits, Circuit 2           92.5%            6.1 $\pm$ 4.2

  : The success rate of the algorithm described in Fig. \[fig:alg\]. The results are generated from 1,500 simulations each of the single and double driver tissues. The prediction success corresponds to the classifier models outputting a final positive prediction which lies on a position which if ablated would terminate the re-entrant circuit. The mean number of jumps refers to the total number of electrogram grid recordings required before reaching a final prediction.

\[tab:res\]

The results indicate that the algorithm is capable at locating simple re-entrant circuits on randomly generated CMP tissues with excellent prediction rates from a small number of 