Advancements in artificial intelligence for the precise diagnosis and treatment of hematological malignancies

TL;DR

This paper reviews how artificial intelligence is improving the diagnosis and treatment of blood cancers, highlighting its benefits and challenges.

Contribution

The paper provides a comprehensive overview of AI applications in hematological malignancies over the past five years.

Findings

AI improves diagnostic accuracy and treatment personalization for blood cancers.

Challenges include poor data quality, limited model interpretability, and restricted clinical translation.

Future progress requires standardized clinical data and multimodal AI integration.

Abstract

血液肿瘤属于高度异质性的恶性疾病，其生物学特征复杂且临床表现多样化，实施精准诊疗显得尤为重要。为进一步提升诊疗精度、提高预后预测准确性、推进个性化医疗，人工智能在血液肿瘤中的应用日趋广泛。本文总结了近五年来人工智能在血液肿瘤的诊断、治疗以及预后预测等方面的应用，对其优势和不足进行了探讨。人工智能可有效提高血液肿瘤精准诊疗的能力，但面临数据质量欠佳、模型可解释性较差以及临床转化有限等瓶颈问题。未来可通过建立临床数据标准、融合多模态信息进行精准诊疗和预后预测、开展模型算法系统化的临床验证等，从而加快人工智能在血液肿瘤临床中的推广和应用。