Pros and cons of artificial intelligence implementation in diagnostic pathology

Paul J van Diest; Rachel N Flach; Carmen van Dooijeweert; Seher Makineli; Gerben E Breimer; Nikolas Stathonikos; Paul Pham; Tri Q Nguyen; Mitko Veta

doi:10.1111/his.15153

Pros and cons of artificial intelligence implementation in diagnostic pathology

Paul J van Diest^*, Rachel N Flach, Carmen van Dooijeweert, Seher Makineli, Gerben E Breimer, Nikolas Stathonikos, Paul Pham, Tri Q Nguyen, Mitko Veta

^*Corresponding author for this work

Research output: Contribution to journal › Review article › peer-review

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Abstract

The rapid introduction of digital pathology has greatly facilitated development of artificial intelligence (AI) models in pathology that have shown great promise in assisting morphological diagnostics and quantitation of therapeutic targets. We are now at a tipping point where companies have started to bring algorithms to the market, and questions arise whether the pathology community is ready to implement AI in routine workflow. However, concerns also arise about the use of AI in pathology. This article reviews the pros and cons of introducing AI in diagnostic pathology.

Original language	English
Pages (from-to)	924-934
Number of pages	11
Journal	Histopathology
Volume	84
Issue number	6
Early online date	3 Mar 2024
DOIs	https://doi.org/10.1111/his.15153
Publication status	Published - May 2024

Keywords

algorithms
diagnostics
digital pathology
implementation
keyword artificial intelligence
machine learning

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10.1111/his.15153Licence: CC BY-NC-ND

Histopathology - 2024 - Diest - Pros and cons of artificial intelligence implementation in diagnostic pathologyFinal published version, 1.32 MBLicence: CC BY-NC-ND

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title = "Pros and cons of artificial intelligence implementation in diagnostic pathology",

abstract = "The rapid introduction of digital pathology has greatly facilitated development of artificial intelligence (AI) models in pathology that have shown great promise in assisting morphological diagnostics and quantitation of therapeutic targets. We are now at a tipping point where companies have started to bring algorithms to the market, and questions arise whether the pathology community is ready to implement AI in routine workflow. However, concerns also arise about the use of AI in pathology. This article reviews the pros and cons of introducing AI in diagnostic pathology.",

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AU - van Diest, Paul J

AU - Flach, Rachel N

AU - van Dooijeweert, Carmen

AU - Makineli, Seher

AU - Breimer, Gerben E

AU - Stathonikos, Nikolas

AU - Pham, Paul

AU - Nguyen, Tri Q

AU - Veta, Mitko

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N2 - The rapid introduction of digital pathology has greatly facilitated development of artificial intelligence (AI) models in pathology that have shown great promise in assisting morphological diagnostics and quantitation of therapeutic targets. We are now at a tipping point where companies have started to bring algorithms to the market, and questions arise whether the pathology community is ready to implement AI in routine workflow. However, concerns also arise about the use of AI in pathology. This article reviews the pros and cons of introducing AI in diagnostic pathology.

AB - The rapid introduction of digital pathology has greatly facilitated development of artificial intelligence (AI) models in pathology that have shown great promise in assisting morphological diagnostics and quantitation of therapeutic targets. We are now at a tipping point where companies have started to bring algorithms to the market, and questions arise whether the pathology community is ready to implement AI in routine workflow. However, concerns also arise about the use of AI in pathology. This article reviews the pros and cons of introducing AI in diagnostic pathology.

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KW - keyword artificial intelligence

KW - machine learning

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JO - Histopathology

JF - Histopathology

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Pros and cons of artificial intelligence implementation in diagnostic pathology

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Keywords

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