Papers by Jacqueline C.k. Lam
An LLM-based Temporal-spatial Data Generation and Fusion Approach for Early Detection of Late Onset Alzheimer’s Disease (LOAD) Stagings Especially in Chinese and English-speaking Populations (2025.findings-emnlp)
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| Challenge: | Existing approaches struggle with temporal-spatial challenges in capturing subtle linguistic shifts across different disease stages. |
| Approach: | They propose a large language model-driven T-S fusion framework that integrates multilingual LLMs, contrastive learning and interpretable marker discovery to revolutionize late onset AD detection. |
| Outcome: | The proposed framework achieves state-of-the-art performance in late onset AD detection while enabling cross-linguistic diagnostics. |