The digital revolution in pathology: Towards a smarter approach to research and treatment
Research output: Contribution to journal › Review article › Contributed › peer-review
Contributors
Abstract
Artificial intelligence (AI) applications in oncology are at the forefront of transforming healthcare during the Fourth Industrial Revolution, driven by the digital data explosion. This review provides an accessible introduction to the field of AI, presenting a concise yet structured overview of the foundations of AI, including expert systems, classical machine learning, and deep learning, along with their contextual application in clinical research and healthcare. We delve into the current applications of AI in oncology, with a particular focus on diagnostic imaging and pathology. Numerous AI tools have already received regulatory approval, and more are under active development, bringing clear benefits but not without challenges. We discuss the importance of data security, the need for transparent and interpretable models, and the ethical considerations that must guide AI development in healthcare. By providing a perspective on the opportunities and challenges, this review aims to inform and guide researchers, clinicians, and policymakers in the adoption of AI in oncology.
Details
Original language | English |
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Pages (from-to) | 241-251 |
Number of pages | 11 |
Journal | Tumori journal : TJ |
Volume | 110 |
Issue number | 4 |
Early online date | 12 Apr 2024 |
Publication status | E-pub ahead of print - 12 Apr 2024 |
Peer-reviewed | Yes |
External IDs
PubMed | 38606831 |
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Mendeley | 1eaf2213-f985-3cd9-895f-bf81078120d6 |
Keywords
Sustainable Development Goals
ASJC Scopus subject areas
Keywords
- Artificial intelligence, deep learning, digital health, digital pathology, machine learning, neural networks, omics, oncology