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All Journal Viva Medika: Jurnal Kesehatan, Kebidanan dan Keperawatan
Muhammad Ahmad Baballe
Nigerian Defence Academy Kaduna
Health Professions Medicine & Pharmacology Nursing Public Health

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Artificial Intelligence in Biomedical Psychology: A Systematic Review of Clinical and Cognitive Applications Annastasya Nabila Elsa Wulandari; Agung Budi Prasetio; Muhammad Ahmad Baballe; Taraknath Paul
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.v18i3.2214

Abstract

Biomedical psychology emphasises psychological and neurocognitive assessment through the integration of biological, neurophysiological, and quantitative behavioural data to support clinical decision-making. However, conventional assessment approaches remain limited by issues of objectivity, scalability, and longitudinal monitoring, prompting the utilisation of artificial intelligence (AI) as a computational tool in clinical and cognitive contexts. This systematic review synthesises the application of AI in biomedical psychology with an explicit focus on assessment functions, rather than intervention or therapy, following the PRISMA 2020 guidelines through a systematic search of four major databases. The included studies cover a variety of clinical and cognitive applications with variations in psychological constructs, data modalities, and AI methods. The synthesis results show that AI is most often used for diagnostic classification, risk screening, and continuous estimation of cognitive functions and dimensional constructs. Differences in assessment objectives between clinical and cognitive domains reveal consistent methodological trade-offs related to model selection, validation strategies, and overfitting risks. As a key contribution, this review presents an assessment-oriented cross-domain synthesis and proposes fit-forpurpose design principles as a conceptual framework for developing robust, interpretable, and clinically relevant AI-based assessment systems
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 Annastasya Nabila Elsa Wulandari Berliana Rahmadhani Isa Ali Ibrahim Purwono Purwono Taraknath Paul