Papers with clinical decision-making
How Can We Diagnose and Treat Bias in Large Language Models for Clinical Decision-Making? (2025.naacl-long)
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| Challenge: | Recent studies have shown that LLMs exhibit social biases inherited from training data. |
| Approach: | They propose a framework for evaluation and mitigation of bias in Large Language Models applied to complex clinical cases using a dataset based on the JAMA Clinical Challenge. |
| Outcome: | The proposed framework employs multiple choice questions and explanations to evaluate gender and ethnicity biases in LLMs. |
A Comprehensive Survey on the Trustworthiness of Large Language Models in Healthcare (2025.findings-emnlp)
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| Challenge: | a survey of large language models in healthcare raises critical concerns around trustworthiness . trustworthy of LLMs in healthcare remains underexplored, lacking a systematic review . |
| Approach: | a new survey examines the trustworthiness of large language models in healthcare . a review examines how each dimension affects reliability and ethical deployment of LLMs . |
| Outcome: | The present study examines the trustworthiness of large language models in healthcare . it identifies key gaps in existing approaches and challenges posed by evolving paradigms . |
Learning What to Ignore: Mitigating Negative Transfer in Medical Knowledge Fusion via Clinical Task-Adaptive Selection (2026.acl-long)
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| Challenge: | Existing approaches to longitudinal EHR modeling struggle to balance structural authority of static ontologies with reasoning flexibility of large language models. |
| Approach: | They propose a framework that integrates external medical knowledge into longitudinal EHR modeling to mitigate clinical data sparsity. |
| Outcome: | The proposed framework outperforms state-of-the-art models on four clinical tasks. |