数字和计算病理学在膀癌中的应用:解决临床紧迫需求的新工具
João Lobo1, Bassel Zein-Sabatto2, Priti Lal3
1Department of Pathology, Portuguese Oncology Institute of Porto (IPO Porto)/Porto Comprehensive Cancer Center Raquel Seruca, Porto, Portugal; Cancer Biology and Epigenetics Group, IPO Porto Research Center (GEBC CI-IPOP), Portuguese Oncology Institute of Porto (IPO Porto)/Porto Comprehensive Cancer Center Raquel Seruca (P.CCC) & CI-IPOP@RISE (Health Research Network), Porto, Portugal; Department of Pathology and Molecular Immunology, ICBAS - School of Medicine and Biomedical Sciences, University of Porto, Porto, Portugal.
概括
计算病理学工具正在通过提高诊断和预测治疗反应来改善膀癌 (BC) 管理. 这些数字病理学算法为个性化BC护理提供了新的策略.
科学领域:
- 在瘤学瘤学.
- 数字病理学数字病理学
- 计算生物学 计算生物学
背景情况:
- 膀癌 (BC) 是一个重大的全球健康挑战,影响患者的发病率,死亡率和医疗保健经济.
- 了解BC的分子亚型和关键驱动因素对于开发有效的治疗策略至关重要.
研究的目的:
- 审查数字病理学中的计算算法,以改善膀癌管理.
- 突出了BC诊断,分期,分级和治疗预测计算工具的进步.
主要方法:
- 关于应用到膀癌数字病理学上的计算算法当前文献的综述.
- 对分子分类,治疗反应预测和治疗标识工具的分析.
主要成果:
- 计算病理学工具提高了诊断准确度,分期和分级在膀癌.
- 数字病理学算法有助于分子亚型化和预测对新辅助疗法的反应.
- 这些计算方法简化了工作流的效率,并提高了临床实践的一致性.
结论:
- 数字病理学中的计算算法代表了膀癌管理的变革性方法.
- 这些工具为更精确的诊断,个性化治疗策略和改善患者治疗结果提供了潜力.
- 数字和计算病理学的整合正在重塑BC的解剖病理学的未来.
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