Cardiovascular autonomic neuromodulation brings together physiological treatment, behavioral support, and emerging computational technologies, but evidence for a treatment should not be mistaken for evidence that artificial intelligence improves it. This critical narrative review examines selected clinical trials and foundational neurotechnology studies alongside ethical and governance guidance. It distinguishes intervention efficacy, the incremental contribution of algorithmic adaptation, and the conditions for responsible implementation. Renal denervation has sham-controlled evidence for blood pressure reduction in selected populations; auricular stimulation and heart rate variability biofeedback have encouraging but more limited clinical evidence. Baroreflex activation requires qualified interpretation because a pivotal hypertension trial did not meet all prespecified primary endpoints. Cortical interfaces, decoded neurofeedback, and cardiac digital twins provide technological or conceptual context without establishing cardiovascular benefit from autonomous algorithmic control. No systematic search, pooled analysis, or formal certainty grading is claimed. The proposed translational framework requires comparison against competent nonadaptive care, clinically justified control limits, interpretable escalation, documented software changes, and meaningful patient participation. It also addresses mental privacy, equitable access, professional responsibility, and the organizational costs of monitoring. Artificial intelligence should therefore be evaluated as a potentially useful adjunct whose clinical and social value must be demonstrated for each intended use, rather than inferred from physiological plausibility or technological sophistication.
Azizi, M., Saxena, M., Wang, Y., Jenkins, J. S., Devireddy, C., Rader, F., Fisher, N. D. L., Schmieder, R. E., Mahfoud, F., Lindsey, J., Sanghvi, K., Todoran, T. M., Pacella, J., Flack, J., Daemen, J., Sharp, A. S. P., Lurz, P., Bloch, M. J., Weber, M. A., … RADIANCE II Investigators and Collaborators. (2023). Endovascular ultrasound renal denervation to treat hypertension: The RADIANCE II randomized clinical trial. JAMA, 329(8), 651-661. https://doi.org/10.1001/jama.2023.0713
Bisognano, J. D., Bakris, G., Nadim, M. K., Sanchez, L., Kroon, A. A., Schafer, J., de Leeuw, P. W., & Sica, D. A. (2011). Baroreflex activation therapy lowers blood pressure in patients with resistant hypertension: Results from the double-blind, randomized, placebo-controlled Rheos pivotal trial. Journal of the American College of Cardiology, 58(7), 765-773. https://doi.org/10.1016/j.jacc.2011.06.008
Böhm, M., Kario, K., Kandzari, D. E., Mahfoud, F., Weber, M. A., Schmieder, R. E., Tsioufis, K., Pocock, S., Konstantinidis, D., Choi, J. W., East, C., Lee, D. P., Ma, A., Ewen, S., Cohen, D. L., Wilensky, R., Devireddy, C. M., Lea, J., Schmid, A., … SPYRAL HTN-OFF MED Pivotal Investigators. (2020). Efficacy of catheter-based renal denervation in the absence of antihypertensive medications (SPYRAL HTN-OFF MED Pivotal): A multicentre, randomised, sham-controlled trial. The Lancet, 395(10234), 1444-1451. https://doi.org/10.1016/s0140-6736(20)30554-7
Corral-Acero, J., Margara, F., Marciniak, M., Rodero, C., Loncaric, F., Feng, Y., Gilbert, A., Fernandes, J. F., Bukhari, H. A., Wajdan, A., Martinez, M. V., Santos, M. S., Shamohammdi, M., Luo, H., Westphal, P., Leeson, P., DiAchille, P., Gurev, V., Mayr, M., … Lamata, P. (2020). The ‘Digital Twin’ to enable the vision of precision cardiology. European Heart Journal, 41(48), 4556-4564. https://doi.org/10.1093/eurheartj/ehaa159
European Parliament & Council of the European Union. (2024). Regulation (EU) 2024/1689 of 13 June 2024 laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). Official Journal of the European Union. https://eur-lex.europa.eu/eli/reg/2024/1689/oj
Ienca, M., & Andorno, R. (2017). Towards new human rights in the age of neuroscience and neurotechnology. Life Sciences, Society and Policy, 13(1), 5. https://doi.org/10.1186/s40504-017-0050-1
Koizumi, A., Amano, K., Cortese, A., Shibata, K., Yoshida, W., Seymour, B., Kawato, M., & Lau, H. (2017). Fear reduction without fear through reinforcement of neural activity that bypasses conscious exposure. Nature Human Behaviour, 1, 0006. https://doi.org/10.1038/s41562-016-0006
McEvoy, J. W., McCarthy, C. P., Bruno, R. M., Brouwers, S., Canavan, M. D., Ceconi, C., Christodorescu, R. M., Daskalopoulou, S. S., Ferro, C. J., Gerdts, E., Hanssen, H., Harris, J., Lauder, L., McManus, R. J., Molloy, G. J., Rahimi, K., Regitz-Zagrosek, V., Rossi, G. P., Sandset, E. C., … Khamidullaeva, G. A. (2024). 2024 ESC Guidelines for the management of elevated blood pressure and hypertension. European Heart Journal, 45(38), 3912-4018. https://doi.org/10.1093/eurheartj/ehae178
Musk, E., & Neuralink. (2019). An integrated brain-machine interface platform with thousands of channels. Journal of Medical Internet Research, 21(10), e16194. https://doi.org/10.2196/16194
Nolan, R. P., Floras, J. S., Harvey, P. J., Kamath, M. V., Picton, P. E., Chessex, C., Hiscock, N., Powell, J., Catt, M., Hendrickx, H., Talbot, D., & Chen, M. H. (2010). Behavioral neurocardiac training in hypertension: A randomized, controlled trial. Hypertension, 55(4), 1033-1039. https://doi.org/10.1161/hypertensionaha.109.146233
Shibata, K., Watanabe, T., Sasaki, Y., & Kawato, M. (2011). Perceptual learning incepted by decoded fMRI neurofeedback without stimulus presentation. Science, 334(6061), 1413-1415. https://doi.org/10.1126/science.1212003
Silvani, A., Calandra-Buonaura, G., Dampney, R. A., & Cortelli, P. (2016). Brain-heart interactions: Physiology and clinical implications. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374(2067), 20150181. https://doi.org/10.1098/rsta.2015.0181
Stavrakis, S., Stoner, J. A., Humphrey, M. B., Morris, L., Filiberti, A., Reynolds, J. C., Elkholey, K., Javed, I., Twidale, N., Riha, P., Varahan, S., Scherlag, B. J., Jackman, W. M., Dasari, T. W., & Po, S. S. (2020). TREAT AF (Transcutaneous Electrical Vagus Nerve Stimulation to Suppress Atrial Fibrillation): A randomized clinical trial. JACC: Clinical Electrophysiology, 6(3), 282-291. https://doi.org/10.1016/j.jacep.2019.11.008
Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. (1996). Heart rate variability: Standards of measurement, physiological interpretation and clinical use. Circulation, 93(5), 1043–1065. https://doi.org/10.1161/01.CIR.93.5.1043
Thayer, J. F., & Lane, R. D. (2009). Claude Bernard and the heart-brain connection: Further elaboration of a model of neurovisceral integration. Neuroscience & Biobehavioral Reviews, 33(2), 81-88. https://doi.org/10.1016/j.neubiorev.2008.08.004
Vasey, B., Nagendran, M., Campbell, B., Clifton, D. A., Collins, G. S., Denaxas, S., Denniston, A. K., Faes, L., Geerts, B., Ibrahim, M., Liu, X., Mateen, B. A., Mathur, P., McCradden, M. D., Morgan, L., Ordish, J., Rogers, C., Saria, S., Ting, D. S. W., … DECIDE-AI expert group. (2022). Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI. Nature Medicine, 28(5), 924-933. https://doi.org/10.1038/s41591-022-01772-9
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Göçer, H., Baş, G., Durukan, A. B., & Yıldırımdemir, H. İ. (2026). Artificial Intelligence in Cardiovascular Autonomic Neuromodulation Evidence Boundaries and Responsible Clinical Translation. AI-Driven Journal of Interdisciplinary Social Research, 1(2), 70-81. https://doi.org/10.5281/zenodo.23928728
Göçer, H., Baş, G., Durukan, A. B., & Yıldırımdemir, H. İ. (2026). Artificial Intelligence in Cardiovascular Autonomic Neuromodulation Evidence Boundaries and Responsible Clinical Translation. AI-Driven Journal of Interdisciplinary Social Research, 1(2), 70-81. https://doi.org/10.5281/zenodo.23928728
Göçer, H., Baş, G., Durukan, A. B., & Yıldırımdemir, H. İ. (2026). Artificial Intelligence in Cardiovascular Autonomic Neuromodulation Evidence Boundaries and Responsible Clinical Translation. AI-Driven Journal of Interdisciplinary Social Research, 1(2), 70-81. doi:10.5281/zenodo.23928728
Göçer, H., Baş, G., Durukan, A. B., & Yıldırımdemir, H. İ. (2026). Artificial Intelligence in Cardiovascular Autonomic Neuromodulation Evidence Boundaries and Responsible Clinical Translation. AI-Driven Journal of Interdisciplinary Social Research, 1(2), 70-81. doi:10.5281/zenodo.23928728
Göçer, Hakan, et al.. "Artificial Intelligence in Cardiovascular Autonomic Neuromodulation Evidence Boundaries and Responsible Clinical Translation." AI-Driven Journal of Interdisciplinary Social Research, vol. 1, no. 2, 2026, pp. 70-81, https://doi.org/10.5281/zenodo.23928728.
Göçer, Hakan, et al.. "Artificial Intelligence in Cardiovascular Autonomic Neuromodulation Evidence Boundaries and Responsible Clinical Translation." AI-Driven Journal of Interdisciplinary Social Research, vol. 1, no. 2, 2026, pp. 70-81, https://doi.org/10.5281/zenodo.23928728.
Göçer, Hakan, et al.. 2026. "Artificial Intelligence in Cardiovascular Autonomic Neuromodulation Evidence Boundaries and Responsible Clinical Translation." AI-Driven Journal of Interdisciplinary Social Research 1, no. 2: 70-81. https://doi.org/10.5281/zenodo.23928728.
Göçer, Hakan, et al.. 2026. "Artificial Intelligence in Cardiovascular Autonomic Neuromodulation Evidence Boundaries and Responsible Clinical Translation." AI-Driven Journal of Interdisciplinary Social Research 1, no. 2: 70-81. https://doi.org/10.5281/zenodo.23928728.
Göçer, H. et al. (2026) 'Artificial Intelligence in Cardiovascular Autonomic Neuromodulation Evidence Boundaries and Responsible Clinical Translation', AI-Driven Journal of Interdisciplinary Social Research, 1(2), pp. 70-81. Available at: https://doi.org/10.5281/zenodo.23928728.
Göçer, H. et al. (2026) 'Artificial Intelligence in Cardiovascular Autonomic Neuromodulation Evidence Boundaries and Responsible Clinical Translation', AI-Driven Journal of Interdisciplinary Social Research, 1(2), pp. 70-81. Available at: https://doi.org/10.5281/zenodo.23928728.
H. Göçer, G. Baş, A. B. Durukan, and H. İ. Yıldırımdemir, "Artificial Intelligence in Cardiovascular Autonomic Neuromodulation Evidence Boundaries and Responsible Clinical Translation," AI-Driven J. Interdiscip. Soc. Res., vol. 1, no. 2, pp. 70-81, 2026, doi: 10.5281/zenodo.23928728.
H. Göçer, G. Baş, A. B. Durukan, and H. İ. Yıldırımdemir, "Artificial Intelligence in Cardiovascular Autonomic Neuromodulation Evidence Boundaries and Responsible Clinical Translation," AI-Driven J. Interdiscip. Soc. Res., vol. 1, no. 2, pp. 70-81, 2026, doi: 10.5281/zenodo.23928728.
Göçer H, Baş G, Durukan AB, Yıldırımdemir Hİ. Artificial Intelligence in Cardiovascular Autonomic Neuromodulation Evidence Boundaries and Responsible Clinical Translation. AI-Driven J. Interdiscip. Soc. Res.. 2026;1(2):70-81.
Göçer H, Baş G, Durukan AB, Yıldırımdemir Hİ. Artificial Intelligence in Cardiovascular Autonomic Neuromodulation Evidence Boundaries and Responsible Clinical Translation. AI-Driven J. Interdiscip. Soc. Res.. 2026;1(2):70-81.
@article{ger2026aijisr,
title = {{Artificial Intelligence in Cardiovascular Autonomic Neuromodulation Evidence Boundaries and Responsible Clinical Translation}},
author = {{Göçer, Hakan and Baş, Gültekin and Durukan, Ahmet Barış and Yıldırımdemir, Halil İbrahim}},
journal = {{AI-Driven Journal of Interdisciplinary Social Research}},
volume = {1},
number = {2},
pages = {70-81},
year = {2026},
doi = {10.5281/zenodo.23928728},
url = {https://aijisr.org/articles/AI-JISR-2026-0014}
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TY - JOUR
TI - Artificial Intelligence in Cardiovascular Autonomic Neuromodulation Evidence Boundaries and Responsible Clinical Translation
AU - Göçer, Hakan
AU - Baş, Gültekin
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AU - Yıldırımdemir, Halil İbrahim
JO - AI-Driven Journal of Interdisciplinary Social Research
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