221 citations · 250 across the 11 of their papers we have counts for
5 papers · 1 filter
Early GVHD Prediction in Liver Transplantation via Multi-Modal Deep Learning on Imbalanced EHR Data
Yushan Jiang, Shuteng Niu, Dongjin Song +5
Graft-versus-host disease (GVHD) is a rare but often fatal complication in liver transplantation, with a very high mortality rate. By harnessing multi-modal deep learning methods t…
Towards Interpretable and Trustworthy Time Series Reasoning: A BlueSky Vision
Kanghui Ning, Zijie Pan, Yushan Jiang +3
Time series reasoning is emerging as the next frontier in temporal analysis, aiming to move beyond pattern recognition towards explicit, interpretable, and trustworthy inference. T…
Multi-modal Time Series Analysis: A Tutorial and Survey
Yushan Jiang, Kanghui Ning, Zijie Pan +7
Multi-modal time series analysis has recently emerged as a prominent research area in data mining, driven by the increasing availability of diverse data modalities, such as text, i…
TS-RAG: Retrieval-Augmented Generation based Time Series Foundation Models are Stronger Zero-Shot Forecaster
Kanghui Ning, Zijie Pan, Yu Liu +7
Large Language Models (LLMs) and Foundation Models (FMs) have recently become prevalent for time series forecasting tasks. While fine-tuning LLMs enables domain adaptation, they of…
TimeXL: Explainable Multi-modal Time Series Prediction with LLM-in-the-Loop
Yushan Jiang, Wenchao Yu, Geon Lee +5
Time series analysis provides essential insights for real-world system dynamics and informs downstream decision-making, yet most existing methods often overlook the rich contextual…