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述评:精神医学机器学习的伦理挑战:聚焦于数据、诊断和治疗。

Commentary: the ethical challenges of machine learning in psychiatry: a focus on data, diagnosis, and treatment.

机构信息

Department of Psychiatry, Yale University, New Haven, CT, USA.

Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA.

出版信息

Psychol Med. 2021 Nov;51(15):2522-2524. doi: 10.1017/S0033291721001008. Epub 2021 May 12.

DOI:10.1017/S0033291721001008
PMID:33975655
Abstract

The clinical interview is the psychiatrist's data gathering procedure. However, the clinical interview is not a defined entity in the way that 'vitals' are defined as measurements of blood pressure, heart rate, respiration rate, temperature, and oxygen saturation. There are as many ways to approach a clinical interview as there are psychiatrists; and trainees can learn as many ways of performing and formulating the clinical interview as there are instructors (Nestler, 1990). Even in the same clinical setting, two clinicians might interview the same patient and conduct very different examinations and reach different treatment recommendations. From the perspective of data science, this mismatch is not one of personal style or idiosyncrasy but rather one of uncertain salience: neither the clinical interview nor the data thereby generated is operationalized and, therefore, neither can be rigorously evaluated, tested, or optimized.

摘要

临床访谈是精神科医生收集数据的程序。然而,临床访谈并不是一个像“生命体征”那样被明确定义的实体,生命体征被定义为血压、心率、呼吸频率、体温和血氧饱和度的测量值。有多少种方法可以进行临床访谈,就有多少种精神科医生的方法;而受训者可以学习到有多少种方法来进行和制定临床访谈,就有多少种方法的指导老师(Nestler,1990)。即使在相同的临床环境中,两位临床医生也可能对同一位患者进行访谈,并进行非常不同的检查,提出不同的治疗建议。从数据科学的角度来看,这种不匹配不是个人风格或特质的问题,而是一个不确定的显著性问题:临床访谈和由此产生的数据都没有被操作化,因此都不能被严格评估、测试或优化。

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Psychol Med. 2021 Nov;51(15):2522-2524. doi: 10.1017/S0033291721001008. Epub 2021 May 12.
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