AI in Medicine: Transforming Diagnostics, Imaging, and Precision Oncology

The recent revolution in artificial intelligence (AI) is transforming numerous scientific fields. In medicine, AI is reshaping how diseases are diagnosed, treated, and studied. By analyzing vast datasets using machine learning and deep learning techniques, AI uncovers patterns and insights that enable earlier diagnoses, precise treatments, and accelerated drug discovery. These innovations are driving significant change in healthcare, particularly in oncology, cardiology, and neurology, where timely interventions and personalized care are crucial for better outcomes. In this talk, we will explore how AI is revolutionizing healthcare, focusing on diagnostics, medical imaging, and radiation oncology. We will highlight advancements that enhance efficiency, accuracy, and personalization in patient care, as well as discuss the essential role physicists play in refining these technologies to ensure they are reliable, precise, and ethical. Specifically, we will examine how AI improves diagnostics by enabling earlier disease detection, often surpassing human experts. In imaging, AI-driven tools enhance image quality, automate segmentation, and identify abnormalities with remarkable precision, transforming radiology. In radiation oncology, AI supports treatment planning, adaptive radiotherapy, and real-time monitoring, ensuring therapies are precise and personalized. Despite its promise, AI faces challenges such as data biases, interpretability issues, and ethical and regulatory concerns. Addressing these obstacles requires interdisciplinary collaboration among physicists, clinicians, and AI researchers to ensure equity, trust, and safety in healthcare applications. This talk aims to inspire engagement with AI's transformative potential in medicine. By showcasing its impact and addressing key challenges, we hope to encourage further exploration of how interdisciplinary efforts can shape the future of patient care.