The digital revolution in pathology: Towards a smarter approach to research and treatment

Research output: Contribution to journalReview articleContributedpeer-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 languageEnglish
Pages (from-to)241-251
Number of pages11
Journal Tumori journal : TJ
Volume110
Issue number4
Early online date12 Apr 2024
Publication statusE-pub ahead of print - 12 Apr 2024
Peer-reviewedYes

External IDs

PubMed 38606831
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