MyndLink: Revolutionizing Chronic Pain Treatment with AI

MyndLink is an advanced, AI-powered system designed to enhance spinal cord stimulation (SCS) treatment outcomes by providing real-time, data-driven recommendations. It helps healthcare providers select the patients most likely to benefit from SCS therapy, reducing the high failure rate of 25-30%1. In the U.S., over 50,000 procedures are performed annually 2; 15,000 cases will likely fail1, as a result of improper or subjective patient selection and a trial-and-error approach. By predicting which SCS patients will benefit the most, MyndLink improves treatment success and lowers healthcare costs by minimizing unsuccessful or repeat procedures.

Market Facts

The global SCS market is expected to grow to 4.12 billion by 2027 with an 8.0% growth rate, driven by the rise in chronic pain, aging populations, and demand for minimally invasive treatments. The North America market represented 73% of the market share in 2023, representing a growth of 3 billion by 2027., distributed among hospitals, ambulatory surgery centers and specialty clinics. 3

How It Works:

  • MyndLink analyzes each patient’s unique medical profile.
  • AI algorithms determine the most effective treatment path.
  • Doctors receive clear insights, enabling personalized care tailored to each patient’s needs.

Revolutionizing Chronic Pain Treatment: Ending the Guesswork in Spinal Cord Stimulation

  • MyndLink predicts which patients will respond positively to SCS therapy.

MyndLink: Transforming Spinal Cord Stimulation (SCS)


Note: MyndLink is ongoing clinical testing; its safety and effectiveness has not yet been established or approved by the FDA.

  1. Dougherty, M. C., Woodroffe, R. W., Wilson, S., Gillies, G. T., Howard, M. A., 3rd, & Carnahan, R. M. (2021). Risk Factors and Survival Analysis of Spinal Cord Stimulator Explantation. Neuromodulation : journal of the International Neuromodulation Society, 24(1), 61–67. https://doi.org/10.1111/ner.13173
  2. 2025 American Academy of Family Physicians, 2025. Despite weak evidence, spinal cord stimulators are big business. https://www.aafp.org/pubs/afp/afp-community-blog/entry/despite-weak-evidence-spinal-cord-stimulators-are-big-business.html?utm_source=chatgpt.com
  3. Fortune Business Insights, 2025. SCS Market Size, Share and Regional Forecast 2020-2027. https://www.aafp.org/pubs/afp/afp-community-blog/entry/despite-weak-evidence-spinal-cord-stimulators-are-big-business.html?utm_source=chatgpt.com
  4. Hadanny, A., Harland, T., Khazen, O., DiMarzio, M., Marchese, A., Telkes, I., Sukul, V., & Pilitsis, J. G. (2022). Development of machine learning–based models to predict treatment response to spinal cord stimulation. Neurosurgery, 90(5), 523–532. https://doi.org/10.1227/neu.0000000000001855
  5. Hariraran, M., et al. (2023). Machine learning in spinal cord stimulation. Retrieved from https://pubmed.ncbi.nlm.nih.gov/37219574/Journal of Neurosurgery: Spine. (2020). Cost analysis of spinal cord stimulation. Retrieved from https://www.jneurosurgery.org