Artificial intelligence in digital pathology — time for a reality check

被引:0
|
作者
Arpit Aggarwal [1 ]
Satvika Bharadwaj [1 ]
Germán Corredor [1 ]
Tilak Pathak [2 ]
Sunil Badve [3 ]
Anant Madabhushi [4 ]
机构
[1] Emory University and Georgia Institute of Technology,Wallace H. Coulter Department of Biomedical Engineering
[2] Atlanta Veterans Affairs Medical Center,Department of Biomedical Engineering
[3] Emory University,Department of Pathology and Laboratory Medicine
[4] Emory University School of Medicine,undefined
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D O I
10.1038/s41571-025-00991-6
中图分类号
学科分类号
摘要
The past decade has seen the introduction of artificial intelligence (AI)-based approaches aimed at optimizing several workflows across many medical specialties. In clinical oncology, the most promising applications include those involving image analysis, such as digital pathology. In this Perspective, we provide a comprehensive examination of the developments in AI in digital pathology between 2019 and 2024. We evaluate the current landscape from the lens of technological innovations, regulatory trends, deployment and implementation, reimbursement and commercial implications. We assess the technological advances that have driven improvements in AI, enabling more robust and scalable solutions for digital pathology. We also examine regulatory developments, in particular those affecting in-house devices and laboratory-developed tests, which are shaping the landscape of AI-based tools in digital pathology. Finally, we discuss the role of reimbursement frameworks and commercial investment in the clinical adoption of AI-based technologies. In this Perspective, we highlight both the progress and challenges in AI-driven digital pathology over the past 5 years, outlining the path forward for its adoption into routine practice in clinical oncology.
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页码:283 / 291
页数:8
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