MILM fine-tunes LLMs on XML-encoded multimodal irregular time series via a two-stage process that exploits informative sampling patterns to achieve top performance on EHR classification datasets.
Medtsllm: Leveraging llms for multimodal medical time series analysis
4 Pith papers cite this work. Polarity classification is still indexing.
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A survey proposing a taxonomy of Injective, Bridging, and Internal Alignment paradigms to evolve TSA into user-driven Time Series Question Answering with LLMs.
COTCAgent combines a code-executing statistics adapter, a weighted knowledge-base chain-of-thought layer, and constrained inquiry to reach 90.47% and 70.41% top-1 accuracy on two medical datasets.
ECG foundation models for signal interpretation and medical LLMs for reasoning can be integrated into agentic systems for real-time cardiovascular intelligence on edge devices.
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From Time Series Analysis to Question Answering: A Survey in the LLM Era
A survey proposing a taxonomy of Injective, Bridging, and Internal Alignment paradigms to evolve TSA into user-driven Time Series Question Answering with LLMs.