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Artificial Intelligence in Bone Marrow Histological Diagnostics: Potential Applications and Challenges.
van Eekelen, Leander; Litjens, Geert; Hebeda, Konnie M.
Afiliação
  • van Eekelen L; Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands.
  • Litjens G; Computational Pathology Group, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.
  • Hebeda KM; Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands.
Pathobiology ; 91(1): 8-17, 2024.
Article em En | MEDLINE | ID: mdl-36791682
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Medula Óssea / Inteligência Artificial Tipo de estudo: Diagnostic_studies / Qualitative_research Limite: Humans Idioma: En Revista: Pathobiology Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Medula Óssea / Inteligência Artificial Tipo de estudo: Diagnostic_studies / Qualitative_research Limite: Humans Idioma: En Revista: Pathobiology Ano de publicação: 2024 Tipo de documento: Article