The future of AI in radiology is shifting from assistive tools to advanced agentic systems that enhance workflow efficiency and diagnostic accuracy. Key to this transformation are three factors: prioritizing people, seamless integration into existing processes, and fostering trust among users. Emerging agentic AI systems will deliver personalized support by learning from radiologists’ behaviors, enabling features like tailored imaging protocols and prioritization of urgent cases. Additionally, the integration of multimodal AI systems will combine data from various sources—such as pathology, genomics, and lab results—providing comprehensive patient analyses for more effective cancer care and treatment planning. This collaborative future relies on the synergy of AI developers, data scientists, and medical professionals to create solutions centering on human needs. The promise of AI-driven radiology lies in collaboration, ensuring innovations enhance the lives of radiologists and patients alike. For insights into the latest advancements in AI in radiology, visit Philips at RSNA 2025.
Source link
