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All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Teknologi Terpadu JOURNAL EDUCATIONAL OF NURSING(JEN)
Nasrullah, Muhammad Hudzaifah
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Computer Science & IT Engineering Nursing

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Journal : JOURNAL EDUCATIONAL OF NURSING(JEN)

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Application of Artificial Intelligence in MRI Image Analysis for Radiological Diagnosis: A Systematic Review Nasrullah, Muhammad Hudzaifah
JOURNAL EDUCATIONAL OF NURSING(JEN) Vol 8, No 1 (2025): Journal Educational of Nursing (JEN)
Publisher : Akademi Keperawatan RSPAD Gatot Soebroto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37430/jen.v8i1.241

Abstract

Purpose: This systematic review critically evaluates recent advances in AI applied to MRI image analysis for radiological diagnosis, emphasizing improvements in diagnostic accuracy and clinical utility.Methodology: A systematic literature review (SLR) was conducted using PRISMA guidelines, employing a PICOC framework. A comprehensive search of the Scopus database was performed, and studies were selected based on strict inclusion/exclusion criteria through screening and synthesis.Findings: The review found that AI techniques significantly enhance MRI diagnostic performance (e.g., better tumor detection) and streamline workflows by automating routine tasks. It also notes growing publication trends from 2020–2024 in this field, reflecting increasing global research interest.Research Limitations: The review is limited by its reliance on a single database (Scopus) and a narrow publication window (2020–2024). Many included studies exhibit data biases and lack comprehensive external validation, which may affect generalizability.Practical Implications: These results suggest that AI integration can improve clinical workflows. The authors emphasize the need for standardized protocols and multidisciplinary collaboration to ensure safe and effective implementation of AI in radiological practice.Originality: This study provides an original contribution by systematically synthesizing the latest literature on AI applications in MRI diagnostics, offering a comprehensive overview of current methods and trends. It fills a gap by critically evaluating recent studies and outlining future research directions.
The Influence of Ultra-Processed Food on Childhood Obesity: A Systematic Review Kusmiati, Evie; Sugandi, Erwin Santoso; Lubis, Syahroni; Hayati, Intan Masita; Nasrullah, Muhammad Hudzaifah
JOURNAL EDUCATIONAL OF NURSING(JEN) Vol 8, No 1 (2025): Journal Educational of Nursing (JEN)
Publisher : Akademi Keperawatan RSPAD Gatot Soebroto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37430/jen.v8i1.243

Abstract

Purpose: This study aims to evaluate the impact of ultra-processed food (UPF) consumption on the risk of obesity in children through a systematic review of studies published between 2019 and 2024.Methodology: Using a Systematic Literature Review (SLR) method with the PRISMA approach, this study screened 319 articles from the Scopus database, ultimately selecting 13 relevant articles based on inclusion and exclusion criteria using the PICOC framework.Findings: A significant correlation exists between UPF consumption and childhood obesity risk. UPFs are associated with elevated BMI, increased waist circumference, nutrient deficiency, and addictive eating patterns. Socioeconomic status, educational setting, and advertising exposure exacerbate these adverse outcomes.Research Limitations: The primary constraints encompass methodological discrepancies across the analyzed studies, an absence of longitudinal data, and restricted applicability of findings to developing nations.Practical Implications: These findings endorse the development of evidence-based nutrition policies, including food labeling and UPF advertising restrictions for children.Originality: This research introduces a novel "3P" intervention framework (Product, Place, Promotion) for regulating UPF consumption, incorporating biological and social variables into a holistic analytical model.
Co-Authors Cahyadi, Dede Christanto, Duta Arief Giantri, Lilik Tiara Hayati, Intan Masita Kusmiati, Evie Lubis, Syahroni Suciana, Ewin Sugandi, Erwin Santoso Widya, Tilly Raycitra