Artificial Intelligence Applications in Cancer Diagnostic Devices: A Focused Review

Abstract

The field of cancer diagnostics is undergoing a rapid transformation due to the advent of artificial intelligence (AI), which has the potential to enhance diagnostic accuracy, efficiency, and the ability to customize care to individual patients. This scoping review explores the landscape of AI technologies, with a particular focus on deep learning, machine learning, and generative models, as well as their integration into medical imaging, digital pathology, and genomic profiling. These technologies offer a multitude of benefits, including higher diagnostic precision, early-stage cancer detection, and personalized treatment strategies. However, the integration of AI into clinical practice is not without its challenges. Concerns regarding data security, the lack of model interpretability, and fragmented regulatory environments persist as significant barriers. This review concludes by emphasizing the pivotal role of artificial intelligence (AI) in the evolution of precision oncology and calls for interdisciplinary collaboration, regulatory clarity, and infrastructure development to support the responsible integration of AI into cancer diagnostics.

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