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Artificial Intelligence and Robotics in Interventional Cardiology: Preparing for a Transformative Future

Journal of Biomedical Research & Environmental Sciences article abstract with citation details, DOI, publication dates, subject areas, full text links, and references.

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Open Access
Article Type Perspective
Subject Medicine Group
OCLC JBRES Record
Dasaad Mulijono*
Issue: Volume6-Issue8
Pages: 1110-1115
Received: 2025-08-03
Accepted: 2025-08-18
Published: 2025-08-19

Abstract

Cardiovascular Disease (CVD) remains the leading cause of death worldwide, despite significant advances in pharmacotherapy and interventional techniques. The emergence of Artificial Intelligence (AI) and robotics represents a transformative leap forward in addressing persistent challenges in interventional cardiology, including operator variability, procedural complexity, and limited access in underserved regions. AI enables real-time data interpretation, lesion assessment, and predictive modelling, while robotic systems enhance precision, reduce operator fatigue, and facilitate remote intervention. Together, these technologies are reshaping the interventional landscape with the promise of safer, more efficient, and more personalized care.

This article reviews the current state of AI and robotic integration in leading cardiovascular centres across the globe, highlights patient and physician benefits, and outlines the critical institutional, educational, and policy preparations required to support responsible adoption. Special emphasis is given to the Indonesian experience at Bethsaida Hospital, which has become a national pioneer in using AI to power its Whole Food Plant-Based Diet (WFPBD) program. Bethsaida has reversed chronic diseases and improved outcomes using scalable digital solutions that leverage AI-driven education, metabolic profiling, and patient engagement tools.

Now, under the leadership of Prof. Dasaad Mulijono (DM), Bethsaida is expanding its technological capabilities into robotic-assisted and AI-guided interventional cardiology, setting a precedent in Southeast Asia for integrative, precision-driven cardiovascular care. This work examines the promise of these technologies and the systemic shifts necessary to ensure they enhance rather than replace the human touch in healing.

FullText HTML FullText PDF DOI: 10.37871/jbres2167 Crossmark

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Copyright

© 2025 Mulijono D. Distributed under Creative Commons CC-BY 4.0 Creative CommonsAttribution

How to cite this article

Mulijono D. Artifi cial Intelligence and Robotics in Interventional Cardiology: Preparing for a Transformative Future. J Biomed Res Environ Sci. 2025 Aug 19; 6(8): 1110-1115. doi: 10.37871/jbres2167, Article ID: JBRES2167, Available at: https:// www.jelsciences.com/articles/jbres2167.pdf

Subject area(s)

Clinical Cardiology

References

  1. Gaidai O, Cao Y, Loginov S. Global Cardiovascular Diseases Death Rate Prediction. Curr Probl Cardiol. 2023 May;48(5):101622. doi: 10.1016/j.cpcardiol.2023.101622. Epub 2023 Jan 29. PMID: 36724816.
  2. Chong B, Jayabaskaran J, Jauhari SM, Chan SP, Goh R, et al. Global burden of cardiovascular diseases: projections from 2025 to 2050. Eur J Prev Cardiol. 2024 Sep 13:zwae281. doi: 10.1093/eurjpc/zwae281. Epub ahead of print. PMID: 39270739.
  3. Roth GA, Mensah GA, Johnson CO, Addolorato G, Ammirati E, et al. GBD-NHLBI-JACC Global Burden of Cardiovascular Diseases Writing Group. Global Burden of Cardiovascular Diseases and Risk Factors, 1990-2019: Update From the GBD 2019 Study. J Am Coll Cardiol. 2020 Dec 22;76(25):2982-3021. doi: 10.1016/j.jacc.2020.11.010. Erratum in: J Am Coll Cardiol. 2021 Apr 20;77(15):1958-1959. doi: 10.1016/j.jacc.2021.02.039. PMID: 33309175; PMCID: PMC7755038.
  4. Khelimskii D, Badoyan A, Krymcov O, Baranov A, Manukian S, et al. AI in interventional cardiology: Innovations and challenges. Heliyon. 2024 Aug 26;10(17):e36691. doi: 10.1016/j.heliyon.2024.e36691. PMID: 39281582; PMCID: PMC11402142.
  5. Göçer H, Durukan AB. The use of artificial intelligence in interventional cardiology. Turk Gogus Kalp Damar Cerrahisi Derg. 2023 Jul 27;31(3):420-421. doi: 10.5606/tgkdc.dergisi.2023.24791. PMID: 37664782; PMCID: PMC10472472.
  6. Subhan S, Malik J, Haq AU, Qadeer MS, Zaidi SMJ, et al. Role of Artificial Intelligence and Machine Learning in Interventional Cardiology. Curr Probl Cardiol. 2023 Jul;48(7):101698. doi: 10.1016/j.cpcardiol.2023.101698. Epub 2023 Mar 14. PMID: 36921654.
  7. Sardar P, Abbott JD, Kundu A, Aronow HD, Granada JF, et al. Impact of Artificial Intelligence on Interventional Cardiology: From Decision-Making Aid to Advanced Interventional Procedure Assistance. JACC Cardiovasc Interv. 2019 Jul 22;12(14):1293-1303. doi: 10.1016/j.jcin.2019.04.048. Erratum in: JACC Cardiovasc Interv. 2019 Aug 26;12(16):1634. doi: 10.1016/j.jcin.2019.07.037. PMID: 31320024.
  8. Rudnicka Z, Pręgowska A, Glądys K, Perkins M, Proniewska K. Advancements in artificial intelligence-driven techniques for interventional cardiology. Cardiol J. 2024;31(2):321-341. doi: 10.5603/cj.98650. Epub 2024 Jan 22. PMID: 38247435; PMCID: PMC11076027.
  9. Itelman E, Witberg G, Kornowski R. AI-Assisted Clinical Decision Making in Interventional Cardiology: The Potential of Commercially Available Large Language Models. JACC Cardiovasc Interv. 2024 Aug 12;17(15):1858-1860. doi: 10.1016/j.jcin.2024.06.013. PMID: 39142763.
  10. Aminorroaya A, Biswas D, Pedroso AF, Khera R. Harnessing Artificial Intelligence for Innovation in Interventional Cardiovascular Care. J Soc Cardiovasc Angiogr Interv. 2025 Mar 18;4(3Part B):102562. doi: 10.1016/j.jscai.2025.102562. PMID: 40230673; PMCID: PMC11993883.
  11. Alsharqi M, Edelman ER. Artificial Intelligence in Cardiovascular Imaging and Interventional Cardiology: Emerging Trends and Clinical Implications. J Soc Cardiovasc Angiogr Interv. 2025 Mar 18;4(3Part B):102558. doi: 10.1016/j.jscai.2024.102558. PMID: 40230671; PMCID: PMC11993891.
  12. Chandramohan N, Hinton J, O'Kane P, Johnson TW. Artificial Intelligence for the Interventional Cardiologist: Powering and Enabling OCT Image Interpretation. Interv Cardiol. 2024 Mar 11;19:e03. doi: 10.15420/icr.2023.13. PMID: 38532946; PMCID: PMC10964291.
  13. De Silva K, Myat A, Strange J, Weisz G. Iterative Improvement and Marginal Gains in Coronary Revascularisation: Is Robot-assisted Percutaneous Coronary Intervention the New Hope? Interv Cardiol. 2020 Dec 16;15:e18. doi: 10.15420/icr.2020.24. PMID: 33376506; PMCID: PMC7756352.
  14. Young L, Khatri J. Robotic Percutaneous Coronary Intervention: The Good, the Bad, and What is to Come. US Cardiol. 2022 Jan 26;16:e02. doi: 10.15420/usc.2020.28R1. PMID: 39600848; PMCID: PMC11588183.
  15. George JC, Varghese V, Madder RD. Robot-Assisted Cardiovascular Interventions. J Soc Cardiovasc Angiogr Interv. 2025 Mar 18;4(3Part B):102568. doi: 10.1016/j.jscai.2025.102568. PMID: 40230678; PMCID: PMC11993876.
  16. Moreno PR, Stone GW, Gonzalez-Lengua CA, Puskas JD. The Hybrid Coronary Approach for Optimal Revascularization: JACC Review Topic of the Week. J Am Coll Cardiol. 2020 Jul 21;76(3):321-333. doi: 10.1016/j.jacc.2020.04.078. PMID: 32674795.
  17. Cook CM, Warisawa T, Howard JP, Keeble TR, Iglesias JF, et al. Algorithmic Versus Expert Human Interpretation of Instantaneous Wave-Free Ratio Coronary Pressure-Wire Pull Back Data. JACC Cardiovasc Interv. 2019 Jul 22;12(14):1315-1324. doi: 10.1016/j.jcin.2019.05.025. PMID: 31320025; PMCID: PMC6645043.
  18. Petraco R, Bahl R, Almeida G, Bandeira D, Seligman H, et al. Can AI Capture and Quantify Clinical Expertise? Implications for Intracoronary Imaging in Percutaneous Coronary Intervention. J Soc Cardiovasc Angiogr Interv. 2025 Mar 18;4(3Part B):102523. doi: 10.1016/j.jscai.2024.102523. PMID: 40230670; PMCID: PMC11993851.
  19. Samant S, Panagopoulos AN, Wu W, Zhao S, Chatzizisis YS. Artificial Intelligence in Coronary Artery Interventions: Preprocedural Planning and Procedural Assistance. J Soc Cardiovasc Angiogr Interv. 2025 Mar 18;4(3Part B):102519. doi: 10.1016/j.jscai.2024.102519. PMID: 40230668; PMCID: PMC11993872.
  20. Khokhar AA, Marrone A, Bermpeis K, Wyffels E, Tamargo M, Fernandez-Avilez F, Ruggiero R, ZÅ‚ahoda-Huzior A, Giannini F, Zelias A, Madder R, Dudek D, Beyar R. Latest Developments in Robotic Percutaneous Coronary Interventions. Interv Cardiol. 2023 Dec 6;18:e30. doi: 10.15420/icr.2023.03. PMID: 38213745; PMCID: PMC10782427.
  21. Biondi-Zoccai G, D'Ascenzo F, Giordano S, Mirzoyev U, Erol Ç, et al. Artificial Intelligence in Cardiology: General Perspectives and Focus on Interventional Cardiology. Anatol J Cardiol. 2025 Apr;29(4):152-163. doi: 10.14744/AnatolJCardiol.2025.5237. PMID: 40151850; PMCID: PMC11965948.
  22. Łajczak P, Eltawansy S, Obi O, Sahin OK, Ayesha A, Almendral J, Selan J, Apolito R, Elashery A, Łajczak A, Buczkowski S, Jóźwik K, Nowakowski P, Janiec J, Żerdziński K, Schincariol M. Robotic percutaneous coronary intervention and the clinical effectiveness debate: Is newer always better? A systematic review and frequentist network meta-analysis. Cardiovasc Revasc Med. 2025 Jul;76:113-120. doi: 10.1016/j.carrev.2025.04.005. Epub 2025 Apr 3. PMID: 40253223.
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