Revitalizing Medical Time Series with Vision-Informed Retrieval: A Vision-Language Perspective

arXiv:2609.34652 · cs.CV · Submitted 2026-09-28 · Read on arXiv

cs.CV

Submitted: 2026-09-28

Updated: 2026-09-28

Comments: Accepted by NeurIPS 2026

Code: https://github.com/Levi-Ackman/ViRe

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Transformer — 35× in this paper · explained in 2 episodes
• Accuracy — 21× in this paper · explained in 1 episode
• Benchmark — 18× in this paper · explained in 2 episodes
• Alignment — 17× in this paper · explained in 1 episode
• Embeddings — 9× in this paper · explained in 2 episodes
• Time Series Forecasting — 9× in this paper · explained in 3 episodes
• Ablation — 8× in this paper · explained in 1 episode
• Clustering — 5× in this paper · explained in 2 episodes
• Representation Learning — 5× in this paper · explained in 2 episodes
• Aggregation — 3× in this paper · explained in 1 episode
• Homogeneity — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Clinical Alignment Ratio — 2× in this paper
• Computational overhead — 2× in this paper · explained in 2 episodes
• Core — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Generalizability — 2× in this paper · explained in 6 episodes
• Institutional Review Board — 2× in this paper
• Interpretability — 2× in this paper · explained in 15 episodes
• Latent Space — 2× in this paper · explained in 7 episodes
• Morphology-Aware Attention Ratio — 2× in this paper
• Tokenization — 2× in this paper · explained in 2 episodes
• Vision-Language Models (VLMs) — 2× in this paper · explained in 6 episodes
• Adaptive Weighting — 1× in this paper · explained in 1 episode
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Feature Selection — 1× in this paper · explained in 4 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Multimodal Fusion — 1× in this paper · explained in 3 episodes
• Non-stationarity — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Semi-supervised Learning — 1× in this paper · explained in 4 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• Transformer Models — 1× in this paper · explained in 2 episodes
• alpha — 1× in this paper · explained in 1 episode
• fNIRS — 1× in this paper · explained in 2 episodes

Sources

• On the Feasibility of Vision-Language Models for Time-Series Classification
• FreEformer: Frequency Enhanced Transformer for Multivariate Time Series Forecasting

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