Volume 1 Number 1 2025
AI in Precision Oncology: Revolutionizing Early Diagnosis, Imaging and Targeted Therapies
Md Sakil Amin1*, Azizur Rahman2, Md Jabir Rashid1
Paradise 1 (1) 1-10 https://doi.org/10.25163/paradise.1110340
Submitted: 29 June 2025 Revised: 06 September 2025 Published: 08 September 2025
Abstract
Artificial intelligence (AI) is changing the landscape of cancer care in exciting ways. It is making strides in early cancer diagnosis, interpreting medical images, and tailoring treatments to individuals' specific needs. By utilizing machine learning and deep learning, AI can sift through complex data sets, such as genetic information and imaging results, to improve the accuracy of diagnoses. This means that cancers can be detected earlier and more accurately, allowing for treatments that are more targeted and effective while aiming to reduce side effects. Introducing AI into clinical practice presents its hurdles. There are significant challenges to address, including limited access to patient data due to privacy laws, the need for standard protocols to validate AI tools, and concerns about the transparency and comprehensibility of these technologies. There is also the critical issue of fairness; we must ensure that all patients have equal access to the benefits of AI in cancer treatment, as economic and social disparities could hinder this. Moreover, integrating AI into current medical practices requires adjustments in infrastructure and additional training for healthcare professionals, which can sometimes meet with resistance. Regulatory approaches also differ around the world; for instance, the European Union has stringent data protection rules, whereas the United States may offer more flexibility. It is crucial to expand databases that combine information from multiple institutions, to improve how we assess uncertainty in AI predictions, and to establish ethical guidelines to ensure that AI can be used safely and fairly.
Keywords: Precision Oncology, Artificial Intelligence, Cancer Imaging, Personalised Treatment, Predictive Analytics.
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