Role of artificial intelligence in haematolymphoid diagnostics

The advent of digital pathology and the deployment of high‐throughput molecular techniques are generating an unprecedented mass of data. Thanks to advances in computational sciences, artificial intelligence (AI) approaches represent a promising avenue for extracting relevant information from complex...

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Bibliographic Details
Published in:Histopathology Vol. 86; no. 1; pp. 58 - 68
Main Authors: Syrykh, Charlotte, Brand, Michiel, Kather, Jakob Nikolas, Laurent, Camille
Format: Journal Article
Language:English
Published: England Wiley Subscription Services, Inc 01.01.2025
Wiley
John Wiley and Sons Inc
Subjects:
Annual Review Issue
Artificial Intelligence
haematopathology
Hematologic Neoplasms - diagnosis
Hematologic Neoplasms - pathology
Hematology
Human health and pathology
Humans
Life Sciences
lymphoma diagnosis
Machine Learning
Pathology
Review
Tissues and Organs
haematopathology
lymphoma diagnosis
artificial intelligence
ISSN:0309-0167, 1365-2559, 1365-2559
Online Access:Get full text
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Summary:The advent of digital pathology and the deployment of high‐throughput molecular techniques are generating an unprecedented mass of data. Thanks to advances in computational sciences, artificial intelligence (AI) approaches represent a promising avenue for extracting relevant information from complex data structures. From diagnostic assistance to powerful research tools, the potential fields of application of machine learning techniques in pathology are vast and constitute the subject of considerable research work. The aim of this article is to provide an overview of the potential applications of AI in the field of haematopathology and to define the role that these emerging technologies could play in our laboratories in the short to medium term. Workflows of artificial intelligence implementations in haematopathology from diagnostic assistance tools (A) to exploratory approaches (B).
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PMCID: PMC11648359
ISSN:0309-0167
1365-2559
1365-2559
DOI:10.1111/his.15327