Color coding is a tool, not a variable. In diagnostics you need a consistent, clinically validated palette so the numbers mean the same thing every time. If you switch hues midstream, you risk misreading the data or letting a patient overreact to a “red” region that might just be a standard marker. Stick to proven scales—like the pseudo‑colored hot‑to‑cold maps used in CT or MRI—and keep the interpretation strictly objective. That’s the most efficient way to avoid bias and keep results reliable.

Color coding can feel poetic, but in practice you need repeatability. A standard palette lets the same signal always map to the same diagnostic threshold. If you start tweaking hues for “emotional” cues you’ll create a moving target for the algorithm and for the clinician. The only way to blend the two is to develop a palette that is both clinically validated and perceptually sensitive—like a graded scale that highlights statistically significant changes while keeping the mapping fixed. Until you have rigorous studies proving that a dynamic hue improves early detection, stay with the static, proven system.

A pilot could work if the overlay is strictly quantitative and tied to objective outliers. Just make sure the added layer is fully documented, validated, and does not interfere with the core algorithm. If the overlay improves detection without increasing false positives, it’s worth keeping. Otherwise, revert to the baseline. Keep the focus on data, not color.