Tumour Mutational Burden Analysis and Immunotherapy Response Prediction: AI-Driven Systems for Personalised Oncology Treatment Optimisation

Authors

  • Kwame Nkrumah Professor of Computer Science, Kwame Nkrumah University of Science and Technology (KNUST)

Keywords:

tumour mutational burden analysis, immunotherapy response prediction, systems, personalised oncology treatment optimisation, machine learning

Abstract

Personalized oncology treatments are becoming increasingly critical in patient care. This development is attributed to the heterogeneity of each patient’s condition. Although different individuals may have the same cancer type, each case potentially develops due to a unique interplay of genetic, environmental, or lifestyle factors. Conventional one-size-fits-all strategies, therefore, may not be adequate to ameliorate the survival or prognosis of such cancer patients.

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Published

30-06-2026

How to Cite

[1]
“Tumour Mutational Burden Analysis and Immunotherapy Response Prediction: AI-Driven Systems for Personalised Oncology Treatment Optimisation”, J. Computational Intel. & Robotics, vol. 6, no. 1, pp. 25–32, Jun. 2026, Accessed: Jun. 04, 2026. [Online]. Available: https://thesciencebrigade.com/jcir/article/view/734