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arXiv 2211.12360cs.CL

GDPR Compliant Collection of Therapist-Patient-Dialogues

Technical University of Darmstadt(达姆施塔特工业大学);Hessian Center for AI (hessian.AI)(黑森人工智能中心);Goethe University(歌德大学);University Hospital Frankfurt(法兰克福大学医院)

Tobias Mayer, Neha Warikoo, Oliver Grimm, Andreas Reif, Iryna Gurevych

英文摘要:

According to the Global Burden of Disease list provided by the World Health Organization (WHO), mental disorders are among the most debilitating disorders.To improve the diagnosis and the therapy effectiveness in recent years, researchers have tried to identify individual biomarkers. Gathering neurobiological data however, is costly and time-consuming. Another potential source of information, which is already part of the clinical routine, are therapist-patient dialogues. While there are some pioneering works investigating the role of language as predictors for various therapeutic parameters, for example patient-therapist alliance, there are no large-scale studies. A major obstacle to conduct these studies is the availability of sizeable datasets, which are needed to train machine learning models. While these conversations are part of the daily routine of clinicians, gathering them is usually hindered by various ethical (purpose of data usage), legal (data privacy) and technical (data formatting) limitations. Some of these limitations are particular to the domain of therapy dialogues, like the increased difficulty in anonymisation, or the transcription of the recordings. In this paper, we elaborate on the challenges we faced in starting our collection of therapist-patient dialogues in a psychiatry clinic under the General Data Privacy Regulation of the European Union with the goal to use the data for Natural Language Processing (NLP) research. We give an overview of each step in our procedure and point out the potential pitfalls to motivate further research in this field.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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