Artificial Intelligence in Bone Marrow Histological Diagnostics: Potential Applications and Challenges.

IF 3.5 4区 医学 Q3 CELL BIOLOGY Pathobiology Pub Date : 2024-01-01 Epub Date: 2023-02-15 DOI:10.1159/000529701
Leander van Eekelen, Geert Litjens, Konnie M Hebeda
{"title":"Artificial Intelligence in Bone Marrow Histological Diagnostics: Potential Applications and Challenges.","authors":"Leander van Eekelen, Geert Litjens, Konnie M Hebeda","doi":"10.1159/000529701","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":19805,"journal":{"name":"Pathobiology","volume":" ","pages":"8-17"},"PeriodicalIF":3.5000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10937040/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pathobiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1159/000529701","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/2/15 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

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.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
人工智能在骨髓组织学诊断中的应用:潜在应用与挑战。
随着常规诊断组织学切片数字化的不断扩大,人工智能(AI)有望应用于病理学,包括骨髓(BM)组织学。在这一视角中,我们描述了未来在骨髓活检的整张切片图像上应用人工智能可支持的潜在诊断任务、可指导的调查以及可回答的问题。这些问题包括细胞系的特征描述、细胞和基质结构的量化以及疾病预测。初步研究表明,利用人工智能检测特定基因型引起的微妙表型变化具有令人兴奋的潜力。我们将以目前使用 BM 活检切片进行人工智能研究的实例来说明讨论的内容。此外,我们还简要讨论了目前在实施人工智能辅助诊断方面所面临的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Pathobiology
Pathobiology 医学-病理学
CiteScore
8.50
自引率
0.00%
发文量
47
审稿时长
>12 weeks
期刊介绍: ''Pathobiology'' offers a valuable platform for the publication of high-quality original research into the mechanisms underlying human disease. Aiming to serve as a bridge between basic biomedical research and clinical medicine, the journal welcomes articles from scientific areas such as pathology, oncology, anatomy, virology, internal medicine, surgery, cell and molecular biology, and immunology. Published bimonthly, ''Pathobiology'' features original research papers and reviews on translational research. The journal offers the possibility to publish proceedings of meetings dedicated to one particular topic.
期刊最新文献
Roles of cancer histology type and HPV genotype in HPV ctDNA detection at baseline in cervical cancer: Implications for tumor burden assessment. Validation of a urine- based proteomics test to predict clinically significant prostate cancer: complementing mpMRI pathway. Nodal T-cell lymphoma transdifferentiated from mantle cell lymphoma with Epstein-Barr virus infection. Human Papilloma Virus-Related Oral Mucosal Lesions in Turkey: A Retrospective Cohort Study. Next-Generation Integrated Sequencing Identifies Poor Prognostic Factors in Patients with MYD88-Mutated Chronic Lymphocytic Leukemia in Taiwan.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1