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一种用于医疗保健领域人工智能和机器人技术的图灵测试的新颖改进。

A novel modification of the Turing test for artificial intelligence and robotics in healthcare.

作者信息

Ashrafian Hutan, Darzi Ara, Athanasiou Thanos

机构信息

Department of Surgery and Cancer and Hamlyn Centre, Imperial College London, UK.

出版信息

Int J Med Robot. 2015 Mar;11(1):38-43. doi: 10.1002/rcs.1570. Epub 2014 Jan 20.

Abstract

BACKGROUND

The increasing demands of delivering higher quality global healthcare has resulted in a corresponding expansion in the development of computer-based and robotic healthcare tools that rely on artificially intelligent technologies. The Turing test was designed to assess artificial intelligence (AI) in computer technology. It remains an important qualitative tool for testing the next generation of medical diagnostics and medical robotics.

METHODS

Development of quantifiable diagnostic accuracy meta-analytical evaluative techniques for the Turing test paradigm.

RESULTS

Modification of the Turing test to offer quantifiable diagnostic precision and statistical effect-size robustness in the assessment of AI for computer-based and robotic healthcare technologies.

CONCLUSIONS

Modification of the Turing test to offer robust diagnostic scores for AI can contribute to enhancing and refining the next generation of digital diagnostic technologies and healthcare robotics.

摘要

背景

提供更高质量全球医疗保健的需求不断增加,导致依赖人工智能技术的计算机化和机器人医疗保健工具的开发相应扩大。图灵测试旨在评估计算机技术中的人工智能。它仍然是测试下一代医学诊断和医疗机器人的重要定性工具。

方法

为图灵测试范式开发可量化诊断准确性的荟萃分析评估技术。

结果

对图灵测试进行修改,以便在评估基于计算机和机器人的医疗保健技术的人工智能时提供可量化的诊断精度和统计效应大小稳健性。

结论

对图灵测试进行修改以提供针对人工智能的稳健诊断分数,有助于改进和完善下一代数字诊断技术和医疗机器人。

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