Artificial intelligence in bone marrow histological diagnostics: potential applications and challenges

被引：5
作者：
van Eekelen, Leander [1 ,2 ]
Litjens, Geert [1 ,2 ]
Hebeda, Konnie [1 ,3 ]
机构：
[1] Radboud Univ Nijmegen, Med Ctr, Dept Pathol, Nijmegen, Netherlands
[2] Radboud Univ Nijmegen, Radboud Inst Hlth Sci, Med Ctr, Computat Pathol Grp, Nijmegen, Netherlands
[3] Radboud Univ Nijmegen, Med Ctr, Dept Pathol, Geert Grootepl Zuid 10, NL-6500 HB Nijmegen, Netherlands
来源：
PATHOBIOLOGY | 2024年 / 91卷 / 01期
基金：
欧洲研究理事会;
关键词：
CUP-LIKE NUCLEI; FEATURES; ASSOCIATION; AGE;
D O I：
10.1159/000529701
中图分类号：
Q2 [细胞生物学];
学科分类号：
071009 ; 090102 ;
摘要：
The expanding digitalization of routine diagnostic histological slides holds a potential to apply artificial intelligence (AI) to pathology, including bone marrow (BM) histology. In this perspective we describe potential tasks in diagnostics that can be supported, investigations that can be guided and questions that can be answered by the future application of AI on whole slide images of BM biopsies. These range from characterization of cell lineages and quantification of cells and stromal structures to disease prediction. First glimpses show an exciting potential to detect subtle phenotypic changes with AI that are due to specific genotypes. The discussion is illustrated by examples of current AI research using BM biopsy slides. In addition, we briefly discuss current challenges for implementation of AI-supported diagnostics.
引用
收藏
页码：8 / 17
页数：10
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