Alhalafi Abdullah, Alqahtani Saif M, Alqarni Naif A, Aljuaid Amal T, Aljaber Ghade T, Alshahrani Lama M, Mushait Hadeel, Nandi Partha A
Department of Family and Community Medicine, University of Bisha, Bisha, SAU.
College of Medicine, University of Bisha, Bisha, SAU.
Cureus. 2024 Apr 22;16(4):e58713. doi: 10.7759/cureus.58713. eCollection 2024 Apr.
Diabetes mellitus, a condition characterized by dysregulation of blood glucose levels, poses significant health challenges globally. This meta-analysis and systematic review aimed to evaluate the effectiveness of artificial intelligence (AI) in managing diabetes, underpinned by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The review scrutinized articles published between January 2019 and February 2024, sourced from six electronic databases: Web of Science, Google Scholar, PubMed, Cochrane Library, EMBASE, and MEDLINE, using keywords such as "Artificial intelligence use in medicine, Diabetes management, Health technology, Machine learning, Diabetic patients, AI applications, and Health informatics." The analysis revealed a notable variance in the prevalence of diabetes symptoms between patients managed with AI models and those receiving standard treatments or other machine learning models, with a risk ratio (RR) of 0.98 (95% CI: 0.88-1.08, I = 0%). Sub-group analyses, focusing on symptom detection and management, consistently showed outcomes favoring AI interventions, with RRs of 0.97 (95% CI: 0.87-1.08, I = 0%) for symptom detection and 0.97 (95% CI: 0.56-1.57, I = 0%) for management, respectively. The findings underscore the potential of AI in enhancing diabetes care, particularly in early disease detection and personalized lifestyle recommendations, addressing the significant health risks associated with diabetes, including increased morbidity and mortality. This study highlights the promising role of AI in revolutionizing diabetes management, advocating for its expanded use in healthcare settings to improve patient outcomes and optimize treatment efficacy.
糖尿病是一种以血糖水平调节异常为特征的疾病,在全球范围内构成了重大的健康挑战。本荟萃分析和系统评价旨在评估人工智能(AI)在糖尿病管理中的有效性,该评价以系统评价和荟萃分析的首选报告项目(PRISMA)指南为依据。该评价审查了2019年1月至2024年2月发表的文章,这些文章来自六个电子数据库:科学网、谷歌学术、PubMed、考克兰图书馆、EMBASE和MEDLINE,使用了“医学中的人工智能应用、糖尿病管理、健康技术、机器学习、糖尿病患者、人工智能应用和健康信息学”等关键词。分析显示,使用人工智能模型管理的患者与接受标准治疗或其他机器学习模型的患者相比,糖尿病症状的患病率存在显著差异,风险比(RR)为0.98(95%CI:0.88 - 1.08,I = 0%)。聚焦于症状检测和管理的亚组分析一致显示,人工智能干预的结果更有利,症状检测的RR为0.97(95%CI:0.87 - 1.08,I = 0%),管理的RR为0.97(95%CI:0.56 - 1.57,I = 0%)。这些发现强调了人工智能在加强糖尿病护理方面的潜力,特别是在疾病早期检测和个性化生活方式建议方面,应对与糖尿病相关的重大健康风险,包括发病率和死亡率的增加。这项研究突出了人工智能在彻底改变糖尿病管理方面的前景作用,倡导在医疗环境中扩大其使用,以改善患者预后并优化治疗效果。