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Review Article

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

  • Paper ID 6
  • Volume 1, Issue 2
  • Pages: 01-05
  • Published Online: May-August 2026
  • 222 Views
Open Access Peer Reviewed

Authors

  • 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.

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Article Information

DOI
No Doi
Published Online
May-August 2026
Pages
01-05
Article Type
Review Article
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Abstract

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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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