Identifying patients suited for renal denervation therapy

A method comprising:

• obtaining, by processing circuitry, pulse information representative of pulses of a patient;
• obtaining, by the processing circuitry, a plurality of values representative of respective patient metrics for the patient;
• applying, by the processing circuitry, the pulse information and the plurality of values to a deep learning model, the deep learning model trained to represent a relationship of the pulse information and the patient metrics to renal denervation efficacy;
• responsive to applying the pulse information and the plurality of values to the deep learning model, obtaining, by the processing circuitry and from the deep learning model, a score indicative of renal denervation efficacy for the patient;
• and
• outputting, by the processing circuitry, an indication of the score indicative of renal denervation efficacy for the patient.

A non-transitory computer-readable medium, comprising instructions that, when executed, cause at least one processor to:

• obtain pulse information representative of pulses of a patient;
• obtain a plurality of values representative of respective patient metrics for the patient;
• apply the pulse information and the plurality of values to the deep learning model, the deep learning model trained to represent a relationship of the pulse information and patient metrics to renal denervation efficacy;
• responsive to applying the pulse information and the plurality of values to the deep learning model, obtain, from the deep learning model, a score indicative of renal denervation efficacy for the patient;
• and
• output an indication of the score indicative of renal denervation efficacy for the patient.