newsNature Machine IntelligenceTrust 88 · LabPublished yesterdayLive · just now
Transfer learning with deployment-covariate recalibration for survival prediction under covariate shift
Nature Machine Intelligence, Published online: 18 August 2026; doi:10.1038/s42256-026-01285-x Pan et al. present CoxRTL, a recalibrated transfer learning strategy that leverages external cohorts to improve survival prediction under covariate shift when target training data are limited and deployment outcomes are unavailable.
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 46%sebp/scikit-survival →
- PossiblePossibly related (embedding) · 46%Parameter-Efficient Vision-Language Adaptation with Continuous Metadata Conditioning for Animal Re-Identification →
- PossiblePossibly related (embedding) · 49%CT-CLIP Representations for Multimodal Lung Cancer Survival Prediction →
- PossiblePossibly related (embedding) · 48%SAGEAgent: A Self-Evolving Agent for Cost-Aware Modality Acquisition in Multimodal Survival Prediction →
Covers
reposebp/scikit-survivalpaperParameter-Efficient Vision-Language Adaptation with Continuous Metadata Conditioning for Animal Re-IdentificationpaperCT-CLIP Representations for Multimodal Lung Cancer Survival PredictionpaperSAGEAgent: A Self-Evolving Agent for Cost-Aware Modality Acquisition in Multimodal Survival Prediction
Related across the graph
paperCT-CLIP Representations for Multimodal Lung Cancer Survival PredictionpaperSAGEAgent: A Self-Evolving Agent for Cost-Aware Modality Acquisition in Multimodal Survival Predictionreposebp/scikit-survivalpaperParameter-Efficient Vision-Language Adaptation with Continuous Metadata Conditioning for Animal Re-Identification