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Patients Reactions to Non-Invasive and Invasive Prenatal Tests: A Machine-Based Analysis from Reddit Posts

机译:患者对非侵入式和侵入式产前检查的反应:来自Reddit帖子的基于机器的分析

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Machine (learning)-based techniques have made substantial advances recently, and there is a general suggestion that they will drive major changes in health care within a few years. Yet, we all suffer from the lack of precise comparative studies on the accuracy of machine-based interpretations of medical data. To fill this gap, in this paper we investigate on the efficacy of using an automated mood analysis methodology to understand how patients react to the prescription to take different kinds of prenatal diagnostic tests (invasive vs non-invasive) and to the corresponding outcomes, based on conversations developed on Reddit. Our study essentially provides answers to research questions concerning: i) the popularity of prenatal diagnosis, ii) the patients' sentiment about different prenatal tests, iii) the existence of a cause-effect relationship between prenatal testing and patients' mood, and iv) the type of dialogues held by patients and physicians on this topic. Nonetheless, a general result emerging from our research is that a machine-based decision loop for now still needs human involvement, at least to alleviate the tension between empirical data and their correct medical interpretation.
机译:最近,基于机器(学习)的技术取得了长足的进步,并且普遍建议它们将在几年内推动医疗保健领域的重大变革。然而,我们都缺乏关于基于机器的医学数据解释准确性的精确比较研究。为了填补这一空白,在本文中,我们将研究使用自动化情绪分析方法来了解患者对处方采取不同种类的产前诊断测试(侵入性与非侵入性)以及相应结果的反应,在Reddit上进行的对话。我们的研究从本质上为以下研究问题提供了答案:i)产前诊断的普及; ii)患者对不同产前检查的看法; iii)产前检查与患者情绪之间存在因果关系; iv)患者和医生就此主题进行的对话类型。尽管如此,从我们的研究中得出的总体结果是,目前基于机器的决策环仍然需要人工参与,至少可以减轻经验数据与其正确的医学解释之间的矛盾。

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