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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) SISFOTENIKA Journal of Information Technology and Computer Science (JOINTECS) Emerging Science Journal Insect (Informatics and Security) : Jurnal Teknik Informatika MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer CYBERNETICS Literasi Hukum Viva Medika: Jurnal Kesehatan, Kebidanan dan Keperawatan Buletin Ilmiah Sarjana Teknik Elektro International Journal of Robotics and Control Systems Jurnal Pengabdian Masyarakat Jurnal Ilmu Komputer dan Teknologi (IKOMTI) SEMINAR NASIONAL PENELITIAN DAN PENGABDIAN KEPADA MASYARAKAT Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesia Journal of Advanced Health Informatics Research Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Control Systems and Optimization Letters
Purwono, Purwono
Universitas Harapan Bangsa
Aerospace Engineering Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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A Scoping Review of Machine Learning Applications in Nursing Practice: Clinical Decision Support, Risk Prediction, and Workflow Optimization Anton Suhendro; Wahyu Caesarendra; Purwono, Purwono
Viva Medika Vol 18 No 3 (2025)
Publisher : LPPM Universitas Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35960/vm.v18i3.2222

Abstract

Machine learning (ML) is rapidly transforming nursing practice by enabling advancements in clinical decision support, risk prediction, and workflow optimization. This scoping review synthesizes evidence from empirical studies, reviews, and implementation reports published between 2018 and 2025, identified through Scopus and ScienceDirect. The findings indicate that supervised learning algorithms, deep learning, and natural language processing are widely utilized for risk assessment, early detection of patient deterioration, and enhancement of administrative efficiency. Natural language processing (NLP) also supports automation of nursing documentation and improved data quality. Despite favorable performance metrics, including AUROC values above 0.85 in many applications, most studies are limited by single-institution data, insufficient external validation, and heterogeneous reporting standards. Major barriers include ethical and legal concerns, data quality issues, algorithmic bias, infrastructural limitations, and limited nurse involvement in model development. Enhancing AI literacy and fostering nurse engagement in system design are highlighted as critical for successful clinical integration. Future research priorities include multicenter validation, development of explainable AI, adoption of standardized reporting guidelines, and interdisciplinary collaboration to address ethical, technical, and regulatory challenges. Overall, this scoping review demonstrates that machine learning offers substantial potential to improve patient outcomes and nursing operations, but responsible adoption requires rigorous validation, transparent governance, and active participation of nursing professionals throughout the technology lifecycle
Artificial Intelligence Applications in Community and Home Nursing Care: A Systematic Literature Review Berliana Rahmadhani; Purwono, Purwono; Muhammad Ahmad Baballe; Isa Ali Ibrahim
Viva Medika Vol 19 No 1 (2026)
Publisher : LPPM Universitas Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35960/vm.v19i1.2235

Abstract

Healthcare systems face increasing demand for community and home nursing care due to population aging, chronic disease prevalence, and hospital resource limitations. Artificial intelligence (AI) has emerged as a supportive technology with potential to enhance nursing practice in decentralized care environments. This systematic literature review synthesizes recent evidence on AI applications in community and home nursing care. The review followed PRISMA 2020 guidelines and analyzed fifteen peer-reviewed studies published between 2022 and 2025. The findings indicate that machine learning–based predictive analytics and decision-support systems are the most frequently implemented technologies. AI applications primarily support risk prediction, remote monitoring, chronic disease management, and workflow optimization. Reported outcomes include improved clinical vigilance, enhanced care coordination, and increased operational efficiency. However, implementation challenges remain, including infrastructure readiness, digital literacy gaps, ethical governance concerns, and data privacy risks. Overall, AI functions as an augmentative tool that strengthens professional nursing judgment rather than replacing it. Sustainable integration in community and home nursing care requires digital competence, regulatory alignment, and human-centered implementation strategies.
Co-Authors Agung Budi Prasetio Agung Pangestu Ahmad Toha Alfian Ma’arif Amanah Wulandari Anggit Wirasto Anggit Wirasto Anton Suhendro Ariefah Khairina Islahati Arif Setia Sandi A. Asmat Burhan Asmat Burhan Bala Putra Dewa Bala Putra Dewa Bala Putra Dewa Bala Putra Dewa Barlian Kristanto Berliana Rahmadhani Burhanuddin bin Mohd Aboobaider Deny Nugroho Triwibowo Dewi Astria Faroek Dimas Febri Kuncoro Dimas Herjuno Eko Ariyanto Elsa Wulandari, Annastasya Nabila Endang Setyawati Hadi Jayusman Hesti Ayu Wahyuni Iin Dyah Indrawati Iis Setiawan Mangkunegara Iis Setyawan Mangku Negara Imam Ahmad Ashari Imam Ahmad Ashari, Imam Ahmad Imam Riadi Imam Riadi Isa Ali Ibrahim Jatmiko Indriyanto Jihad Rahmawan Khoirun Nisa Khoirun Nisa Khoirun Nisa Lutviana Lutviana Lutviana Mangku Negara, Iis Setiawan Mangkunegara, Iis Setiawan Marlia Hafny Afrilies Maya Ruhtiani Muchammad Naseer Muhammad Ahmad Baballe Muhammad Baballe Ahmad Muhammad Haikal Satria Muntiari, Novita Ranti Musafa Widagdo Pramesti Dewi Qazi Mazhar ul Haq Rahmadhani, Berlina Riska Suryani Riyanarto Sarno Rosyid Ridlo Al-Hakim Rubaeah, Siti Rusydi Umar Safar Dwi Kurniawan Salah, Wael A. Sandi Najib Iskandar Sharkawy , Abdel-Nasser Slamet Slamet Sony Kartika Wibisono Sony Kartika Wibisono Sony Kartika Wibisono Sony Kartika Wibisono Supriyatin Supriyatin Tohari Ahmad Tusaria Tri Wahyu Ningrum Wahyu Caesarendra Wahyu Rahmaniar Windu Gata Wulandari, Annastasya Nabila Elsa Yanuar Zulardiansyah Arief Yudhistira , Aimar Yuris Tri Naili Yuris Tri Naili Yuslena Sari, Yuslena Yusuf Fadlila Rahman