Advances in Bone Marrow Evaluation.

Artificial intelligence Aspirate Bone marrow Machine learning Trephine biopsy

Journal

Clinics in laboratory medicine
ISSN: 1557-9832
Titre abrégé: Clin Lab Med
Pays: United States
ID NLM: 8100174

Informations de publication

Date de publication:
Sep 2024
Historique:
medline: 2 8 2024
pubmed: 2 8 2024
entrez: 1 8 2024
Statut: ppublish

Résumé

Evaluation of bone marrow aspirate smear and trephine biopsy specimens is critical to the diagnosis of benign and malignant hematologic conditions. Digital pathology has the potential to revolutionize bone marrow assessment through implementation of artificial intelligence for assisted and automated evaluation, but there remain many barriers toward this implementation. This article reviews the current state of digital evaluation of bone marrow aspirate smears and trephine biopsies, recent research using machine learning models for automated specimen analysis, an outline of the advantages and barriers facing clinical implementation of artificial intelligence, and a potential vision of artificial intelligence-associated bone marrow evaluation.

Identifiants

pubmed: 39089749
pii: S0272-2712(24)00016-7
doi: 10.1016/j.cll.2024.04.005
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

431-440

Informations de copyright

Copyright © 2024 Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Disclosure O. Pozdnyakova is a consultant for Scopio and serves as a speaker for Sysmex.

Auteurs

Joshua E Lewis (JE)

Department of Pathology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02215, USA.

Olga Pozdnyakova (O)

The Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA. Electronic address: olga.pozdnyakova@pennmedicine.upenn.edu.

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Classifications MeSH