Abstract

The rise of digital data and computing power have contributed to significant advancements in artificial intelligence (AI), leading to the use of classification and prediction models in health care to enhance clinical decision-making for diagnosis, treatment and prognosis. However, such advances are limited by the lack of reporting standards for the data used to develop those models, the model architecture, and the model evaluation and validation processes. Here, we present MINIMAR (MINimum Information for Medical AI Reporting), a proposal describing the minimum information necessary to understand intended predictions, target populations, and hidden biases, and the ability to generalize these emerging technologies. We call for a standard to accurately and responsibly report on AI in health care. This will facilitate the design and implementation of these models and promote the development and use of associated clinical decision support tools, as well as manage concerns regarding accuracy and bias.

中文翻译：

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MINIMAR（医疗人工智能报告的最小信息）：制定医疗保健人工智能报告标准。

摘要

数字数据和计算能力的兴起促进了人工智能 (AI) 的重大进步，导致在医疗保健中使用分类和预测模型来增强诊断、治疗和预后的临床决策。然而，由于缺乏用于开发这些模型的数据、模型架构以及模型评估和验证过程的报告标准，这些进步受到了限制。在这里，我们提出了 MINIMAR（医学人工智能报告的最小信息），这是一项提案，描述了理解预期预测、目标人群和隐藏偏见所需的最少信息，以及推广这些新兴技术的能力。我们呼吁制定一个标准来准确、负责任地报告医疗保健领域的人工智能。