transformer-model

This paper presents a two-stage transformer framework for predicting the risk and timing of acute exacerbations of COPD using raw waveform data from home ventilators, demonstrating improved performance over baseline models.

This paper investigates using in-context learning with the TabPFN model to predict perceived neighborhood walkability based on built environment features for mobility-impaired older adults, achieving higher performance than baseline models and employing SHAP-IQ for interaction analysis.