人工智能集成多omics数据用于精确分层和药物耐药性预测乳腺癌
Deshui Ran1, Jing Li1, Mengmeng Zhao1
1Department of Imaging, Jinan Second People's Hospital, Jinan, China.
Frontiers in oncology
|September 29, 2025
概括
人工智能 (AI) 增强了早期乳腺癌 (BC) 诊断和分子亚型. 多模式人工智能改善治疗策略和药物发现,以获得更好的患者结果.
科学领域:
- 在瘤学瘤学.
- 医疗成像医学成像
- 生物信息学是一种生物信息学.
背景情况:
- 乳腺癌 (BC) 是一种普遍存在的恶性瘤,具有诊断和分子亚型化挑战.
- 晚期诊断和BC异质性影响治疗疗效和生存率.
- 目前的早期检测方法缺乏特异性和有效的生物标志物.
研究的目的:
- 审查人工智能 (AI) 在乳腺癌诊断和治疗中的应用.
- 突出AI在早期检测,分子亚型化和预测治疗反应方面的作用.
- 探索AI在药物发现和耐药性研究中对个性化医学的潜力.
主要方法:
- 对人工智能在乳腺癌中的应用进行系统审查.
- 分析综合成像,病理学和多omics数据的多模式AI.
- 评估人工智能模型的诊断准确性,亚型和治疗预测.
主要成果:
- 人工智能在癌症检测方面实现了放射科医生级别的准确性,减少了工作量并提高了特异性.
- 多模式人工智能能够实现强大的分子亚型和免疫微环境量化.
- 人工智能有助于预测免疫治疗反应和耐药性,支持个性化治疗.
结论:
- 人工智能显著提高了乳腺癌的诊断,提供更早的检测和更高的准确性.
- 人工智能通过精确的分子亚型和响应预测来促进个性化治疗策略.
- 人工智能整合有望在乳腺癌管理和药物开发方面取得进展.
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