研究人工智能对乳腺癌管理个性化的影响:一项系统研究
Solmaz Sohrabei1, Hamid Moghaddasi2, Azamossadat Hosseini3
1Department of Health Information Technology and Management, Medical Informatics, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
BMC cancer
|July 18, 2024
概括
人工智能 (AI) 通过分析复杂的遗传数据来提高乳腺癌的精确瘤学. 人工智能模型准确地预测治疗反应和患者的存活率,改善了个性化癌症管理.
科学领域:
- 在瘤学瘤学.
- 生物信息学是一种生物信息学.
- 医疗信息学 医疗信息学
背景情况:
- 精密瘤学旨在根据个体遗传特征量身定制乳腺癌治疗方法,以改善结果.
- 人工智能 (AI) 具有提高瘤学治疗选择和患者管理的潜力.
- 及时和专业的治疗对于有效的乳腺癌护理至关重要.
研究的目的:
- 系统地审查人工智能在个性化乳腺癌管理中的应用.
- 评估人工智能模型在预测治疗反应,预后和生存方面的有效性.
- 确定用于乳腺癌精度瘤学的常见AI技术.
主要方法:
- 对PubMed,Embase,Scopus和Web of Science数据库进行系统审查 (2023年9月).
- 关键词包括"乳腺癌"",人工智能"",精密瘤学"和同义词.
- 排除描述性,定性,综述性和非英语研究;使用SJR,JBI和PRISMA2020指南进行质量评估.
主要成果:
- 选择了46项研究,重点关注人工智能在个性化乳腺癌管理中的应用.
- 深度学习方法 (17项研究) 在预测治疗反应和预后方面显示出令人满意的结果.
- 机器学习方法 (26项研究) 改善了乳腺癌的分类,查,诊断和预后,平均AUC为0.91,准确度,灵敏度,特异性和精度为90-96%.
结论:
- 人工智能通过识别omics和遗传数据中的模式,有效地协助乳腺癌治疗管理.
- 人工智能驱动的基因和蛋白质模式分析对复杂疾病管理具有变革潜力.
- 深度神经网络和机器学习是推动个性化乳腺癌护理的关键人工智能工具.
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