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EHRBench：用于临床决策的自动化和可靠的基于EHR的基准EHRBench: An Automated and Reliable EHR-based Benchmark for Clinical Decision Making with LLMs

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以下内容为 AI 自动翻译，英文原文附后供参考。

摘要

研究人员推出了EHRBench，这是一种新颖的自动化基准，旨在评估大型语言模型（LLMs）在临床决策中的应用。该基准利用近100万个来自实际电子健康记录（EHR）的问答项，允许对LLMs在诊断、治疗和预后等关键任务上的全面评估。通过分析性能趋势和识别改进领域，EHRBench旨在提高LLMs在医疗应用中的可靠性和有效性。

Researchers have introduced EHRBench, a novel automated benchmark designed to evaluate large language models (LLMs) specifically in the context of clinical decision-making. This benchmark utilizes nearly 1 million question-and-answer items sourced from actual electronic health records (EHRs), allowing for a comprehensive assessment of LLMs on vital tasks such as diagnosis, treatment, and prognosis. By analyzing performance trends and identifying areas for improvement, EHRBench aims to enhance the reliability and effectiveness of LLMs in healthcare applications.

要点

  1. EHRBench为评估临床环境中的LLMs提供了强大的框架。

    EHRBench provides a robust framework for evaluating LLMs in clinical settings.

  2. 该基准基于真实世界数据，确保相关性和适用性。

    The benchmark is based on real-world data, ensuring relevance and applicability.

  3. 它突出了LLMs的优缺点，指导未来的改进。

    It highlights both strengths and weaknesses of LLMs, guiding future improvements.

为何重要

EHRBench的开发代表了提高医疗保健中AI可靠性的重要一步，这对患者安全和有效治疗至关重要。通过提供标准化的评估方法，它可以帮助确保LLMs为现实世界的临床应用做好充分准备。

The development of EHRBench represents a significant step towards improving the reliability of AI in healthcare, which is critical for patient safety and effective treatment. By providing a standardized evaluation method, it can help ensure that LLMs are adequately prepared for real-world clinical applications.

按谁的角度看

产品经理

对于产品经理而言，EHRBench提供了一个有价值的工具，用于评估医疗保健中AI产品的性能，使基于实证数据的产品开发和改进决策更加有效。

For product managers, EHRBench offers a valuable tool for assessing the performance of AI products in healthcare, enabling better decision-making regarding product development and enhancements based on empirical data.

开发者

开发人员和工程师可以利用EHRBench了解LLMs在临床环境中的具体能力和局限性，从而指导他们构建更有效和可靠的医疗AI解决方案。

Developers and engineers can leverage EHRBench to understand the specific capabilities and limitations of LLMs in clinical contexts, guiding them in building more effective and reliable AI solutions for healthcare.

学生与求职者

对于学生和求职者而言，EHRBench突显了AI与医疗保健日益交汇的趋势，提供了参与塑造临床决策未来的创新技术和方法的机会。

For students and job-seekers, EHRBench highlights the growing intersection of AI and healthcare, presenting opportunities to engage with innovative technologies and methodologies that are shaping the future of clinical decision-making.

覆盖来源

来源标题与摘录保留原文，以便核对与追溯。

  • arXiv cs.AI

    EHRBench: An Automated and Reliable EHR-based Benchmark for Clinical Decision Making with LLMs

    Researchers developed EHRBench, an automated benchmark that evaluates large language models (LLMs) in clinical decision-making using nearly 1 million question-and-answer items derived from real electronic health records (EHRs). This tool assesses LLMs on critical tasks such as diagnosis, treatment, and prognosis, highlighting performance trends and areas needing improvement.