Artificial Intelligence and Digital Innovations in Oncology
Artificial Intelligence (AI) and digital health technologies are rapidly transforming cancer diagnosis, treatment planning, and patient management by enhancing accuracy, efficiency, and predictive capabilities. Machine learning algorithms are now widely used in radiology and pathology to detect tumors at earlier stages through advanced imaging analysis, improving diagnostic precision while reducing human error. AI-powered tools assist clinicians in interpreting complex genomic data, identifying actionable mutations, and recommending personalized treatment strategies based on real-world evidence and clinical trial databases. Digital pathology, automated image recognition, and predictive analytics are streamlining workflows and enabling faster clinical decision-making. In radiation oncology, AI enhances treatment planning by optimizing dose distribution and minimizing damage to surrounding healthy tissues. Additionally, wearable devices and remote monitoring platforms support continuous patient tracking, improving symptom management and adherence to therapy, especially in tele-oncology settings. Big data integration from electronic health records (EHRs), genomics, and clinical outcomes is enabling predictive modeling for survival rates, treatment responses, and recurrence risks. Emerging trends also include AI-driven drug discovery, which accelerates identification of novel therapeutic targets and reduces development timelines. However, challenges such as data privacy, algorithm bias, regulatory compliance, and integration into clinical practice require careful governance. This session will highlight cutting-edge AI applications, digital transformation strategies, real-world implementation case studies, and ethical considerations that are shaping the next generation of oncology care and redefining how cancer is detected, treated, and managed globally.