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Calibration-First Cross-Cohort Multimodal Temporal Learning for Transferable Asthma-Risk Forecasting
Not provided in the abstract
multimodaltemporal learningrisk forecastingcalibration
2609.35795
Builder Relevance
1h ago70%
Abstract
This paper presents CALIBRA, a framework for reliable asthma deterioration forecasting across varying patient populations and sensor modalities.
Reality Card
Core Claim
CALIBRA achieved a mean target-test AUPRC of 0.224, demonstrating effective risk prediction despite cohort variability.
Method / Result
Mean AUROC was 0.717.
Limitations
The results do not establish clinical effectiveness and require external validation on harmonized real asthma data.
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