Artificial Intelligence for Diagnosis Stunting: A Systematic Review - Aisyah Sabrina, Syarifah Tiara; Melinda, Eza; Nuraziza, Shafira; Machalli, Muchammad Jalaluddin (The International Journal of Medical Science and Health Research, 2024)
Background: One issue that arises from chronic malnutrition during the first 1000 days of life is childhood stunting. The World Health Organization (WHO) reported that in 2020, 22% of children under the age of five worldwide were stunted. Methods: This systematic review focused on full-text English literature published between 2014 and 2024 using the PRISMA 2020 guidelines. Editorials and review pieces published in the same journal as the submission without a DOI were not accepted. The literature was compiled using PubMed, ScienceDirect, and SagePub, among other online venues. Result: We compiled a total of 8 papers, 4 of which came from PubMed, 1 of which came from SAGEPUB and 1 of which came from SCIENCE DIRECT. We included eight research that met the criteria. Conclusion: In summary, research to develop a diagnostic system for child stunting can be pursued further. To begin with, many researchers have opted to use the forward chaining approach while doing research that involves developing diagnostic systems