A Cross-Dataset Audit of Discrimination and Conformal Prediction Coverage in Keystroke-Based Parkinson's Disease Classi cation

Typing dynamics are being investigated as a digital behavioral marker for Parkinson's disease (PD), but the cross-dataset reliability of typing-based classi ers remains uncertain. We evaluated four public datasets (475 par ticipants; 270 with PD and 205 controls) across 12 transfer directions using split conformal prediction targeting 90% marginal coverage. In all three pri mary directions, coverage was below the 0.90 target and the one-sided tests remained signi cant after Holm correction: 0.598 (95% CI, 0.4830.704) for Tappy[->]MIT, 0.850 (0.7880.899) for MIT[->]Tappy, and 0.732 (0.6840.777)

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