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Review Open Access

Artificial intelligence in oncology: Current status and possibilities (Review)

  • Authors:
    • Abhavya Roy
    • Apurva Bhoyar
    • Ashok Ahirwar
    • Yogesh Pawade
    • Nilesh Chandra
  • View Affiliations / Copyright

    Affiliations: University College of Medical Sciences, Guru Teg Bahadur Hospital, Delhi 110095, India, Department of Biochemistry, All India Institute of Medical Sciences, Nagpur, Maharashtra 441108, India, Department of Laboratory Medicine, All India Institute of Medical Sciences, New Delhi 110029, India, Indian Council of Medical Research, Ansari Nagar, New Delhi 110029, India
    Copyright: © Roy et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY 4.0].
  • Article Number: 20
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    Published online on: February 19, 2026
       https://doi.org/10.3892/mi.2026.304
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Abstract

Artificial intelligence (AI) is increasingly reshaping oncology by enhancing diagnostic accuracy, improving prognostication and enabling personalized treatment planning. The present review aimed to critically synthesize the contemporary landscape of AI applications across cancer imaging, digital pathology, clinical outcome prediction, chemotherapy and radiotherapy. Recent advances in machine learning and deep learning, particularly convolutional neural networks and transformer‑based architectures, have demonstrated robust performance in lesion detection, tumour grading, survival prediction and treatment optimization, in several instances approaching or exceeding expert‑level accuracy. Despite these advances, translation into routine clinical practice remains limited due to dataset bias, limited generalizability, the lack of standardized data protocols, insufficient interpretability and regulatory barriers. Ethical challenges related to fairness, transparency and equitable access are especially relevant in low‑ and middle‑income countries. Emerging frontiers, including multimodal AI, foundation models, federated learning, and explainable AI, provide potential solutions to these challenges. Multidisciplinary collaboration, rigorous prospective validation and robust ethical governance will be essential to realize the full potential of AI in advancing precision oncology and improving global cancer outcomes.
View Figures

Figure 1

AI in oncological pathology: AI
integration across digital pathology, biomarker analysis, tumour
diagnosis and grading, and predictive prognostication, highlighting
how multimodal data processing supports pattern recognition and
outcome prediction to enable precision oncology. AI, artificial
intelligence.
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Copy and paste a formatted citation
Spandidos Publications style
Roy A, Bhoyar A, Ahirwar A, Pawade Y and Chandra N: Artificial intelligence in oncology: Current status and possibilities (Review). Med Int 6: 20, 2026.
APA
Roy, A., Bhoyar, A., Ahirwar, A., Pawade, Y., & Chandra, N. (2026). Artificial intelligence in oncology: Current status and possibilities (Review). Medicine International, 6, 20. https://doi.org/10.3892/mi.2026.304
MLA
Roy, A., Bhoyar, A., Ahirwar, A., Pawade, Y., Chandra, N."Artificial intelligence in oncology: Current status and possibilities (Review)". Medicine International 6.2 (2026): 20.
Chicago
Roy, A., Bhoyar, A., Ahirwar, A., Pawade, Y., Chandra, N."Artificial intelligence in oncology: Current status and possibilities (Review)". Medicine International 6, no. 2 (2026): 20. https://doi.org/10.3892/mi.2026.304
Copy and paste a formatted citation
x
Spandidos Publications style
Roy A, Bhoyar A, Ahirwar A, Pawade Y and Chandra N: Artificial intelligence in oncology: Current status and possibilities (Review). Med Int 6: 20, 2026.
APA
Roy, A., Bhoyar, A., Ahirwar, A., Pawade, Y., & Chandra, N. (2026). Artificial intelligence in oncology: Current status and possibilities (Review). Medicine International, 6, 20. https://doi.org/10.3892/mi.2026.304
MLA
Roy, A., Bhoyar, A., Ahirwar, A., Pawade, Y., Chandra, N."Artificial intelligence in oncology: Current status and possibilities (Review)". Medicine International 6.2 (2026): 20.
Chicago
Roy, A., Bhoyar, A., Ahirwar, A., Pawade, Y., Chandra, N."Artificial intelligence in oncology: Current status and possibilities (Review)". Medicine International 6, no. 2 (2026): 20. https://doi.org/10.3892/mi.2026.304
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