For decades, diagnostics have required data generation and then interpretation. Computational approaches, however, could generate new diagnostics from *existing* data - images, radiology, EEGs, and genomics. This panel will delve into advancements in AI-driven diagnostic tools, emphasizing their ability to analyze complex data sets and predict clinical outcomes with unprecedented accuracy. Panelists will discuss how "in silico" diagnostics are transforming traditional workflows, improving early detection, and enabling more personalized approaches to patient care. The conversation will also address the challenges of scaling these technologies, including regulatory hurdles, integration into existing healthcare systems, and reimbursement.