Jehad Feras AlSamhori, Abdel Rahman Feras AlSamhori, Leslie Anne Duncan, Ahmad Qalajo, Hamzeh Feras Alshahwan, Mohammed Al-abbadi, Mohammad Al Soudi, Rihane Zakraoui, Ahmad Feras AlSamhori, Saif Aldeen Alryalat, Abdulqadir J. Nashwan
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引用次数: 0
摘要
乳腺癌的全球性影响和高死亡率推动了人们对人工智能(AI)应用的兴趣。人工智能的模式识别和决策能力为检测、诊断、个性化治疗、风险评估和预防带来了希望。人工智能增强型乳房 X 射线照相术改善了筛查和早期检测。人工智能可帮助放射科医生进行病变检测和诊断,但假阳性的问题依然存在。此外,人工智能还彻底改变了乳腺成像技术,可协助乳房X光检查、生物标记物评估、淋巴结检测和结果预测。人工智能,特别是通过深度学习算法,推进了对风险和治疗反应的基因洞察。人工智能指导的放射治疗规划使协作治疗方法受益匪浅。然而,人工智能所面临的挑战包括数据隐私、伦理和监管问题,这些问题必须加以解决,以确保在维护医疗信任的同时成功实施人工智能。因此,本评论综述了人工智能对乳腺癌的影响。
Artificial intelligence for breast cancer: Implications for diagnosis and management
Breast cancer's global impact and high mortality rates drive interest in Artificial intelligence (AI) applications. AI's pattern recognition and decision-making abilities offer promise in detection, diagnosis, personalized treatment, risk assessment, and prevention. Screening and early detection are improved by AI-enhanced mammography. AI aids radiologists in lesion detection and diagnosis, though concerns about false positives persist. In addition, AI revolutionizes breast imaging, assisting in reading mammograms, biomarker assessment, lymph node detection, and outcome prediction. Genetic insights into risk and treatment response are advanced by AI, particularly through deep learning algorithms. Collaborative treatment approaches benefit from AI-guided radiotherapy planning. However, challenges of AI include data privacy, ethics, and regulatory issues that must be navigated to ensure successful AI implementation while upholding healthcare trust. Therefore, this commentary provided an overview of implication of AI in breast cancer.