Evaluator-Dependent Patient-Adaptive ECG Lead-Channel Allocation
Xiaoyang Li, Zeyan Tao
Abstract
The diagnostic value of an ECG channel depends on the model that interprets it. We test whether adaptive acquisition retains its advantage over fixed protocols when that model changes. Two policies developed with a logistic evaluator are frozen and assessed with a masked waveform ResNet1D, using exhaustive, metric-matched fixed comparators. On PTB-XL, replacing the evaluator reverses the mean adaptive advantage in negative log-likelihood and Brier score across the tested budgets, while calibration responds less uniformly. The shift persists with common fixed references and broader training-mask exposure. Training a policy against the stronger evaluator partly recovers the lost advantage. These retrospective exploratory results show that acquisition quality cannot be assessed independently of the downstream evaluator and motivate validating adaptive policies with the model intended for diagnosis.
Create a lesson
Related papers
PhysVGGT: Feed-Forward Dense Physical Property Estimation from A Single Image
Sneha Paul, Guile Wu, Bingbing Liu et al.
NormLift: From Lifted Features To Semantic Reliability In 3D Gaussian Splatting
Yihan Zang, Da Li, Dominik Engel et al.
Decodable but Misrouted: Sparse Features Uncover a Readout Gap in Vision-Language Models for Harmful Meme Detection
Girish A. Koushik, Diptesh Kanojia, Helen Treharne
Copy What Is Seen, Generate What Is Not: Training-Free Anomaly-Aware Video Restoration
Zhida Qu, Shengchao Chen
Using OCR Heads to Verbalize Image Semantics
Sheridan Feucht, Benno Krojer, Sarah Wang et al.
DISTA-Net++: Rethinking Infrared Small Target Unmixing Beyond Sub-Pixel Separation
Mengze Xu, Zhu Liu, Weidong Sheng et al.