Abstract:
Background: The integration of artificial intelligence (AI) into oncology practice is transforming cancer care delivery. By leveraging large-scale data, machine learning algorithms, and advanced analytics, AI has the potential to address key challenges in cancer management and improve overall quality of care.
Objective: This presentation explores the current and emerging roles of AI across the cancer care continuum and its impact on enhancing the quality of care.
Methods: A comprehensive review of the literature was conducted, focusing on AI applications in early detection, diagnosis, treatment planning, monitoring, and survivorship care. Key examples from recent clinical studies and technological developments were analysed to demonstrate AI's contribution to patient-centred care.
Results: AI improves diagnostic accuracy through advanced image analysis and digital pathology, enabling earlier and more precise cancer detection. In treatment planning, AI facilitates personalised therapeutic decisions by integrating genomic, clinical, and radiological data. Predictive algorithms facilitate risk stratification and toxicity prediction, while AI-powered monitoring systems enable the real-time assessment of treatment response and the early detection of recurrence. Collectively, these applications contribute to improved survival rates, reduced treatment-related morbidity, and enhanced patient satisfaction.
Conclusion: AI represents a powerful adjunct to traditional oncology care, with significant potential to enhance quality, safety, and efficiency across the cancer care continuum. Ongoing research, ethical considerations, and multidisciplinary collaboration will be essential to optimise AI integration into routine clinical practice.
