Papers by Fen Zhao
A Continued Pretrained LLM Approach for Automatic Medical Note Generation (2024.naacl-short)
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Dong Yuan, Eti Rastogi, Gautam Naik, Sree Prasanna Rajagopal, Sagar Goyal, Fen Zhao, Bharath Chintagunta, Jeffrey Ward
| Challenge: | HEAL is the first continuously trained LLaMA2-based LLM for medical conversations . despite the success of LLMs in general capabilities, they often fall short in niche domains like healthcare . |
| Approach: | They propose a 13B LLaMA2-based LLM that is purpose-built for medical conversations and measured on automated scribing. |
| Outcome: | The HEAL LLM outperforms GPT-4 and PMC-LLaMA in PubMedQA with 78.4% accuracy and parity with GPT-LLAMA in generating medical notes. |
Knowledge Graph Embedding with Hierarchical Relation Structure (D18-1)
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| Challenge: | Existing knowledge graph embedding models embed entities and relations into latent vectors without leveraging rich information from relation structure. |
| Approach: | They extend existing KGE models to learn knowledge representations by leveraging relation structure . authors say their approach is capable of extending other KGEs . |
| Outcome: | The proposed approach can extend existing KGE models, and validates against baselines. |
TreeMAN: Tree-enhanced Multimodal Attention Network for ICD Coding (2022.coling-1)
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| Challenge: | Existing methods to automatically assign ICD codes ignore crucial information contained in structured medical data, which is hard to be captured from the noisy clinical notes. |
| Approach: | They propose to use a Tree-enhanced multimodal attention network to fuse tabular features and textual features into multimodal representations by enhancing the text representations with tree-based features. |
| Outcome: | The proposed method outperforms state-of-the-art methods on two MIMIC datasets. |