Recentering responsible and explainable artificial intelligence research on patients: implications in perinatal psychiatry.
Recentering responsible and explainable artificial intelligence research on patients: implications in perinatal psychiatry.
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DOI：
10.3389/fpsyt.2023.1321265
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发表时间：
2023
影响因子：
4.7
通讯作者：
Benda, Natalie C.
中科院分区：
文献类型：
--
作者：
Turchioe, Meghan Reading;Hermann, Alison;Benda, Natalie C.
在围产期抑郁症（PD）诊断不足和治疗不足的背景下，人工智能（AI）解决方案有望帮助预测和治疗PD。在不久的将来，围产期患者可能会在临床决策过程中、在其患者门户中，或者通过提供心理治疗的人工智能聊天机器人与AI进行交互。潜在的人工智能应用的增加引发了关于负责任的人工智能和可解释人工智能（XAI）的讨论。然而，当前关于负责任的人工智能（RAI）的讨论在将患者视为与人工智能积极互动的参与者这方面考虑有限。因此，我们提出一种以患者为中心，而非与患者相关联的负责任的人工智能和可解释人工智能的方法，该方法将自主性、有益性、公正性、信任、隐私和透明度确定为医疗专业人员和患者应坚持的核心概念。我们提供了实证证据，表明这些原则受到患者的高度重视。我们进一步提出了可能的设计方案，以维护这些原则，并承认迫切需要对实际应用进行进一步研究以维护这些原则。
In the setting of underdiagnosed and undertreated perinatal depression (PD), Artificial intelligence (AI) solutions are poised to help predict and treat PD. In the near future, perinatal patients may interact with AI during clinical decision-making, in their patient portals, or through AI-powered chatbots delivering psychotherapy. The increase in potential AI applications has led to discussions regarding responsible AI and explainable AI (XAI). Current discussions of RAI, however, are limited in their consideration of the patient as an active participant with AI. Therefore, we propose a patient-centered, rather than a patient-adjacent, approach to RAI and XAI, that identifies autonomy, beneficence, justice, trust, privacy, and transparency as core concepts to uphold for health professionals and patients. We present empirical evidence that these principles are strongly valued by patients. We further suggest possible design solutions that uphold these principles and acknowledge the pressing need for further research about practical applications to uphold these principles.
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影响因子：
4.8
作者：
Betts, Kim S.;Kisely, Steve;Alati, Rosa
通讯作者：
Alati, Rosa
影响因子：
6.9
作者：
Brandon, Anna R.;Shivakumar, Geetha;Sadler, John Z.
通讯作者：
Sadler, John Z.
DOI：
10.3390/s23020634
发表时间：
2023-01-05
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Chaddad A;Peng J;Xu J;Bouridane A
通讯作者：
Bouridane A
影响因子：
9.5
作者：
Davidson L;Boland MR
通讯作者：
Boland MR
DOI：
10.1093/jamia/ocab238
发表时间：
2021-11-02
影响因子：
6.4
作者：
Benda, Natalie C.;Novak, Laurie L.;Ancker, Jessica S.
通讯作者：
Ancker, Jessica S.