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دسته بندی:
یادگیری ماشین - machine learning
سال انتشار:
2019
عنوان انگلیسی مقاله:
The risks of risk: Regulating the use of machine learning for psychosis prediction
ترجمه فارسی عنوان مقاله:
ریسک ریسک ها: تنظیم استفاده از یادگیری ماشین برای پیش بینی روان پریشی
منبع:
Sciencedirect - Elsevier - International Journal of Law and Psychiatry, 66 (2019) 101479: doi:10:1016/j:ijlp:2019:101479
نویسنده:
Paolo Corsico⁎
چکیده انگلیسی:
Recent advances in Machine Learning (ML) have the potential to revolutionise psychosis prediction and psychiatric
assessment. This article has two objectives. First, it clarifies which aspects of English Law are relevant in
order to regulate the use of ML in clinical research on psychosis prediction. It is argued that its lawful implementation
will depend upon the legal requirements regarding the balance between potential harms and
benefits, particularly with reference to: (i) any additional risks introduced by the use of ML for data analysis and
outcome prediction; and (ii) the inclusion of vulnerable research populations such as minors or incapacitated
adults. Second, this article investigates how clinical prediction via ML might affect the practice of risk assessment
under mental health legislation, with reference to English Law. It is argued that there is a potential for virtuous
applications of clinical prediction in psychiatry. However, reaffirming the distinction between psychosis risk and
risk of harm is paramount. Establishing psychosis risk and assessing a persons risk of harm are discrete practices,
and so should remain when using artificial intelligence for psychiatric assessment. Evaluating whether clinical
prediction via ML might benefit individuals with psychosis will depend on which risk we try to assess and on
what we try to predict, whether this is psychosis transition, a psychotic relapse, self-harm and suicidality, or
harm to others.
Keywords: Psychosis | Machine learning | Risk | Prediction | Regulation
قیمت: رایگان
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