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All Journal JURNAL PENELITIAN PERAWAT PROFESIONAL Science Midwifery Jurnal Peduli Masyarakat Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Pengabdian Masyarakat Asia AJAD : Jurnal Pengabdian kepada Masyarakat Public Health and Safety International Journal (PHASIJ) Java Nursing Journal Jurnal Suaka Insan Mengabdi LITERA ABDI: Jurnal Pengabdian Masyarakat
Fiana, Marista
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Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Health Professions Languange, Linguistic, Communication & Media Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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Artificial intelligence in cardiac nursing practice: A systematic review of applications, challenges, and patient outcomes Wahananingtyas, Nova Listya; Aprilio, ⁠Rachmad; Risnadhia, Risnadhia; Fiana, Marista; Padhila, Fevi; Azhar, Sabrina Rahmatillah
Science Midwifery Vol 13 No 6 (2026): February: Health Sciences and related fields
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/midwifery.v13i6.2250

Abstract

Cardiovascular diseases remain the leading cause of global mortality, requiring innovative approaches to improve cardiac care. This systematic review aimed to examine the applications of Artificial Intelligence (AI) in cardiac nursing practice, identify implementation challenges, and assess its impact on patient outcomes. The review was conducted in accordance with PRISMA 2020 guidelines, using PubMed, ScienceDirect, CINAHL, and Web of Science. Original studies published between 2020 and 2025 that explicitly addressed nursing roles in cardiac care were included. Eleven studies met the inclusion criteria and were appraised using the Joanna Briggs Institute (JBI) tools. The results show that AI applications, including ChatGPT and machine learning models, support cardiac nursing through clinical decision support, patient education, risk prediction, and home-based monitoring. These applications were associated with improved nursing efficiency, enhanced patient self-management, early detection of clinical deterioration, and potential reduction in hospitalization. However, challenges such as data accuracy, ethical concerns, algorithm transparency, and limited digital literacy among nurses were consistently reported. In conclusion, AI has strong potential to enhance evidence-based and patient-centered cardiac nursing practice. Successful integration requires ethical governance, adequate training, and interdisciplinary collaboration to ensure safe and effective implementation.
Co-Authors Ade Komariah Agus Indarto Al Farisi, Muhammad Farhan Aprilio, ⁠Rachmad Ardinata, Ardinata Azhar, Sabrina Rahmatillah Azzi, Muhamad Fahmi Basrowi Fiana, Risnadhia Fikri, Riki Ukhtul Fikri, Riri Ukhtul Hanifah Hernawati Ichwanudin, Muhamad Kaligis, Yosua Aldrin Kurnia, Nia Marlina Maharani, Silvia Malinda, Tia Masnawati, Nasty Masnawati, Naty Mesya, Mesya Muhammad Alghifari Budiman Muhka, Reni muti'ah, Eva Ningsih, Rastia Nova Maulana Nur, Sulistia Padhila, Fevi Priyana Putra, Rausan Fikri Ratna Esmayanti Rezeki, Muhamad Alif Riki Ukhtul Fitri Risnadhia, Risnadhia Sa’adah, Nene Novi Silvia Sa’adah, Neneng Novi Silvia Selvianita, Defi Siti Masitoh Siti Romlah Subroto, Desty Endrawati Uli Wildan Nuryanto Wahananingtyas, Nova Listya Wulan Asih, Sari Zahra, Nisrina