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Current AI technologies in cancer diagnostics and treatment

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Abstract

Cancer continues to be a significant international health issue, which demands the invention of new methods for early detection, precise diagnoses, and personalized treatments. Artificial intelligence (AI) has rapidly become a groundbreaking component in the modern era of oncology, offering sophisticated tools across the range of cancer care. In this review, we performed a systematic survey of the current status of AI technologies used for cancer diagnoses and therapeutic approaches. We discuss AI-facilitated imaging diagnostics using a range of modalities such as computed tomography, magnetic resonance imaging, positron emission tomography, ultrasound, and digital pathology, highlighting the growing role of deep learning in detecting early-stage cancers. We also explore applications of AI in genomics and biomarker discovery, liquid biopsies, and non-invasive diagnoses. In therapeutic interventions, AI-based clinical decision support systems, individualized treatment planning, and AI-facilitated drug discovery are transforming precision cancer therapies. The review also evaluates the effects of AI on radiation therapy, robotic surgery, and patient management, including survival predictions, remote monitoring, and AI-facilitated clinical trials. Finally, we discuss important challenges such as data privacy, interpretability, and regulatory issues, and recommend future directions that involve the use of federated learning, synthetic biology, and quantum-boosted AI. This review highlights the groundbreaking potential of AI to revolutionize cancer care by making diagnostics, treatments, and patient management more precise, efficient, and personalized.

Graphical Abstract

This graphical abstract schematically illustrates the progressive role of artificial intelligence in the cancer treatment continuum.
Title
Current AI technologies in cancer diagnostics and treatment
Authors
Ashutosh Tiwari
Soumya Mishra
Tsung-Rong Kuo
Publication date
01-12-2025
Publisher
BioMed Central
Published in
Molecular Cancer / Issue 1/2025
Electronic ISSN: 1476-4598
DOI
https://doi.org/10.1186/s12943-025-02369-9
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Image Credits
Colon cancer illustration/© (M) KATERYNA KON / SCIENCE PHOTO LIBRARY / Getty Images