E pluribus unum: The diagnostician

Artificial Intelligence (AI) is a transformative force that is reshaping the very foundations of diagnostic medicine. As AI-driven technologies increasingly blur the boundaries between image interpretation and tissue analysis, the rationale for maintaining radiology and pathology as separate specialties becomes less compelling. A merger into a unified specialty - diagnostic medicine - could offer new opportunities for synergy, enabling clinicians to deliver more accurate, timely, and personalized care. This paper argues that the convergence of radiology and pathology is not only a likely development but also important for the future of precision medicine. The integration of imaging, histopathology, and molecular diagnostics will support a new generation of diagnosticians equipped to navigate complex data landscapes and guide clinical decision-making with deeper insight. • AI as a Catalyst for Specialty Convergence Artificial Intelligence is accelerating the integration of radiology and pathology, challenging the rationale for maintaining them as separate disciplines. • Emergence of the Diagnostician The paper introduces the concept of a hybrid medical professional — the “diagnostician” — trained in imaging, pathology, molecular diagnostics, and AI. • Case Studies Demonstrate Feasibility Real-world examples from UCLA, Proscia, and the National Academies illustrate successful implementation of integrated diagnostic workflows. • Educational Reform is Essential A unified curriculum and integrated residency programs are proposed to train future diagnosticians, supported by new certification pathways and CME modules. • Stakeholder Support Across Sectors Clinicians, hospital administrators, industry leaders, and educators recognize the value of integrated diagnostics for improving outcomes and operational efficiency. • Strategic Opportunities Outweigh Challenges Data integration, interdisciplinary collaboration, infrastructure development, and ethical governance are framed as opportunities for innovation and transformation. • Call to Action for Healthcare Systems The authors advocate for deliberate planning and investment to prepare for a future where diagnostic medicine is unified, AI-enhanced, and patient-centered.