https://ojs3.poltekkes-mks.ac.id/index.php/medperawat/issue/feed 2026-04-30T10:15:11+08:00 Yulianto M yulianto@poltekkes-mks.ac.id Open Journal Systems <p><strong>Media Keperawatan</strong> : Politeknik Kesehatan Makassar. <a href="https://issn.lipi.go.id/terbit/detail/1530505494" target="_blank" rel="noopener">E-ISSN 2622-0148</a>, <a href="https://issn.lipi.go.id/terbit/detail/1395973308" target="_blank" rel="noopener">P-ISSN 2087-0035</a>. Kebutuhan publikasi aspirasi ilmiah dari kalangan penggiat kesehatan khususnya Dosen dalam hal ini dosen untuk Keperawatan semakin meningkat, oleh karena itu Jurnal Media Keperawatan muncul sebagai salah satu sarana untuk publikasi segala bentuk ide, hasil penelitian serta kajian ilmiah yang berhubungan dengan pengembangan Keperawatan dan kesehatan pada umumnya. Jurnal Media Keperawatan diterbitkan oleh Jurusan Keperawatan Poltekkes Makassar dengan periode terbit 2 kali dalam setahun, yaitu terbit di bulan Juni dan Desember.</p> https://ojs3.poltekkes-mks.ac.id/index.php/medperawat/article/view/1616 2025-12-22T15:23:47+08:00 Muhammad Rezky muhammadrezky@uin-alauddin.ac.id Kurnia Rahma Syarif kurniarahmasyarif@poltekkes-mks.ac.id Yulianto M yulianto@poltekkes-mks.ac.id

<p>Artificial Intelligence (AI) has seen rapid development and is increasingly implemented in various aspects of healthcare. This technology has the potential to improve diagnostic accuracy, enhance service efficiency, and support data-driven clinical decision-making. This study aims to systematically review the implementation of AI in the healthcare sector, focusing on its applications, challenges, and associated ethical and social implications. A systematic literature review was conducted using 11 peer-reviewed articles sourced from PubMed and major scientific journals. Articles were selected through predefined inclusion criteria and analyzed thematically to extract key themes. The results show that AI has been widely applied in medical image analysis, automated diagnosis, and clinical prediction, particularly through the use of deep learning models such as convolutional neural networks (CNN). These models demonstrated high performance in detecting diseases like cancer, diabetic retinopathy, and pulmonary conditions. However, implementation challenges remain, including limited interpretability of models, issues with data quality and algorithmic bias, and ethical concerns surrounding patient data privacy. In conclusion, AI holds significant promise for transforming healthcare, but its responsible and effective adoption requires robust regulatory frameworks, adequate infrastructure, and strong collaboration between AI systems and medical professionals.</p>

2026-04-30T00:00:00+08:00 Hak Cipta (c) 2026 Media Keperawatan: Politeknik Kesehatan Makassar