Rohlfsen Cory, Shannon Kevin, Parsons Andrew S
Department of Medicine, University of Nebraska Medical Center, Omaha, USA.
University of Virginia School of Medicine, Charlottesville, USA.
J Gen Intern Med. 2025 Sep 18. doi: 10.1007/s11606-025-09868-x.
Navigating uncertainty is fundamental to sound clinical decision-making. With the advent of artificial intelligence, mathematical approximations of disease states-expressed as entropy-offer a novel approach to quantify and communicate uncertainty. Although entropy is well established in fields like physics and computer science, its technical complexity has delayed its routine adoption in clinical reasoning. In this narrative review, we adhere to Shannon's definition of entropy from information processing theory and examine how it has been used in clinical decision-making over the last 15 years. Grounding our analysis in decision theory-which frames decisions in terms of states, acts, consequences, and preferences-we evaluated 20 studies that employed entropy. Our findings reveal that entropy is predominantly used to quantify uncertainty rather than directly guiding clinical actions. High-stakes fields such as oncology and radiology have led the way, using entropy to improve diagnostic accuracy and support risk assessment, while applications in neurology and hematology remain largely exploratory. Notably, no study has yet translated entropy into an operational, evidence-based decision-support framework. These results point to entropy's value as a quantitative tool in clinical reasoning, while also highlighting the need for prospective validation and the development of integrated clinical tools.
应对不确定性是合理临床决策的基础。随着人工智能的出现，用熵来表示的疾病状态的数学近似值为量化和传达不确定性提供了一种新方法。尽管熵在物理学和计算机科学等领域已得到广泛应用，但其技术复杂性阻碍了它在临床推理中的常规应用。在这篇叙述性综述中，我们遵循信息处理理论中香农对熵的定义，并研究了过去15年中熵在临床决策中的应用方式。我们以决策理论为分析基础——决策理论从状态、行为、后果和偏好的角度来构建决策——评估了20项使用熵的研究。我们的研究结果表明，熵主要用于量化不确定性，而不是直接指导临床行动。肿瘤学和放射学等高风险领域处于领先地位，利用熵来提高诊断准确性并支持风险评估，而在神经病学和血液学中的应用在很大程度上仍处于探索阶段。值得注意的是，尚未有研究将熵转化为一个可操作的、基于证据的决策支持框架。这些结果表明了熵作为临床推理中一种定量工具的价值，同时也凸显了进行前瞻性验证和开发综合临床工具的必要性。
