# 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.

## Key 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。