Integrating large language models into time series predictions in healthcare applications
Predicting patient outcomes in intensive care units (ICUs) is challenging due to the irregularity and sparsity of medical data. Traditional time-series models usually fail to capture all patient information, while large language models (LLMs) lack temporal awareness and are prone to hallucinat...
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Format: | Final Year Project |
Language: | English |
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Nanyang Technological University
2025
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Online Access: | https://hdl.handle.net/10356/183936 |
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