Diagnostics companies often focus on performance metrics before they have fully explained the use case. AUC, sensitivity and specificity matter, but they do not answer the commercial question alone.
Strategic buyers and investors also want to know where the test fits in the care pathway, who pays, what clinical decision changes, what comparator defines value, and what evidence a buyer or investor can trust.
For AI-enabled healthcare platforms, the evidence story should also address data quality, reproducibility, model drift, regulatory pathway and the practical economics of adoption.