Deep learning in cancer diagnosis, prognosis and treatment selection

Deep learning is a subdiscipline of artificial intelligence that uses a machine learning technique called artificial neural networks to extract patterns and make predictions from large data sets. We also assess the current limitations and challenges for the application of deep learning in precision oncology, including the lack of phenotypically rich data and the need for more explainable deep learning models.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

• 1 The increasing adoption of deep learning across healthcare domains together with the availability of highly characterised cancer datasets has accelerated research into the utility of deep learning in the analysis of the complex biology of cancer.
• 2 While early results are promising, this is a rapidly evolving field with new knowledge emerging in both cancer biology and deep learning.
• 3 In this review, we provide an overview of emerging deep learning techniques and how they are being applied to oncology.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

This summary is based on publicly available metadata and abstract. For the full research paper, visit the original source: