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Review Article

AI-Enabled Electrocardiography for Screening and Diagnosis of Peripartum Cardiomyopathy: A Mini Review

Kunj Rajeshbhai Ghantiwala1 Ruchik Kevadiya2 Nishit Choksi3

1 Medicine Department, GMERS Medical College Navsari, India. 2 Internal Medicine Department, Henry Ford Rochester Hospital/Wayne State University, USA. 3 Cardiology Department, Henry Ford Rochester Hospital/Wayne State University, USA.

Published Online: May-August 2026

Pages: 01-05

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Abstract

Peripartum cardiomyopathy (PPCM) is an uncommon but potentially life-threatening form of heart failure occurring in late pregnancy or early postpartum period. Early diagnosis remains challenging due to nonspecific symptoms and limited access to echocardiography in primary settings. Artificial intelligence (AI)-enabled electrocardiography (ECG) has emerged as a promising, low-cost, and scalable tool for early cardiac dysfunction detection. This mini review explores the role of AI-ECG in screening and diagnosing PPCM, its current evidence base, limitations, and future clinical integration.

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References

  • [1]. Adedinsewo DA, Morales-Lara AC, Afolabi BB, Kushimo OA, Mbakwem AC, Ibiyemi KF, et al. Artificial intelligence guided screening

  • for cardiomyopathies in an obstetric population: a pragmatic randomized clinical trial. Nat Med. 2024 Oct;30(10):2897-2906.

  • doi:10.1038/s41591-024-03243-9. PMID:39223284. PMCID:PMC11485252.

  • [2]. Cho Y, Yoon M, Kim J, Lee JH, Oh IY, Lee CJ, et al. Artificial intelligence-based electrocardiographic biomarker for outcome prediction

  • in patients with acute heart failure: prospective cohort study. J Med Internet Res. 2024 Jul 3;26:e52139. doi:10.2196/52139.

  • PMID:38959500. PMCID:PMC11255523.

  • [3]. Bachtiger P, Petri CF, Scott FE, Park SR, Kelshiker MA, Sahemey HK, et al. Point-of-care screening for heart failure with reduced ejection

  • fraction using artificial intelligence during ECG-enabled stethoscope examination in London, UK: a prospective, observational,

  • multicentre study. Lancet Digit Health. 2022 Feb;4(2):e117-e125. doi:10.1016/S2589-7500(21)00256-9. PMID:34998740.

  • PMCID:PMC8789562.

  • [4]. Rushlow DR, Croghan IT, Inselman JW, Thacher TD, Friedman PA, Yao X, et al. Clinician adoption of an artificial intelligence algorithm

  • to detect left ventricular systolic dysfunction in primary care. Mayo Clin Proc. 2022 Nov;97(11):2076-2085.

  • doi:10.1016/j.mayocp.2022.04.008. PMID:36333015.

Citations

Kunj Rajeshbhai Ghantiwala, Ruchik Kevadiya, Nishit Choksi, “R AI-Enabled Electrocardiography for Screening and Diagnosis of Peripartum Cardiomyopathy: A Mini Review”, Indian Journal of Clinical and Medical Research, Volume 01, Issue 02, May-August 2026, PP: 01-05.

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Licensing

© 2026 The Author(s). Published by Fifth Dimension Research Publication.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

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