Mooghal Mehwish, Nasir Saad, Arif Aiman, Khan Wajiha, Rashid Yasmin Abdul, Vohra Lubna M
Section Breast Surgery, Department of Surgery, Aga Khan University Hospital Karachi, Sindh, Pakistan.
Department of Medicine, Aga Khan University Hospital Karachi, Sindh, Pakistan.
Cancer Inform. 2024 Sep 29;23:11769351241272389. doi: 10.1177/11769351241272389. eCollection 2024.
This narrative review explores the burgeoning field of Artificial Intelligence (AI)-driven Breast Cancer (BC) survival prediction, emphasizing the transformative impact on patient care. From machine learning to deep neural networks, diverse models demonstrate the potential to refine prognosis accuracy and tailor treatment strategies. The literature underscores the need for clinician integration and addresses challenges of model generalizability and ethical considerations. Crucially, AI's promise extends to Low- and Middle-Income Countries (LMICs), presenting an opportunity to bridge healthcare disparities. Collaborative efforts in research, technology transfer, and education are essential to empower healthcare professionals in LMICs. As we navigate this frontier, AI emerges not only as a technological advancement but as a guiding light toward personalized, accessible BC care, marking a significant stride in the global fight against this formidable disease.
本叙述性综述探讨了人工智能(AI)驱动的乳腺癌(BC)生存预测这一新兴领域,强调其对患者护理的变革性影响。从机器学习到深度神经网络,各种模型都显示出提高预后准确性和定制治疗策略的潜力。文献强调了临床医生整合的必要性,并讨论了模型通用性和伦理考量等挑战。至关重要的是,人工智能的前景延伸到低收入和中等收入国家(LMICs),为缩小医疗保健差距提供了契机。在研究、技术转让和教育方面的合作努力对于增强低收入和中等收入国家医疗保健专业人员的能力至关重要。在我们探索这一前沿领域时,人工智能不仅作为一项技术进步出现,而且作为实现个性化、可及的乳腺癌护理的指引之光,标志着在全球抗击这一可怕疾病的斗争中迈出了重要一步。