Explainable AI in Healthcare

被引：75

作者：

Pawar, Urja ^{[1
]}

O'Shea, Donna ^{[1
]}

Rea, Susan ^{[1
]}

O'Reilly, Ruairi ^{[1
]}

机构：

[1] Cork Inst Technol, Cork, Ireland

来源：

2020 INTERNATIONAL CONFERENCE ON CYBER SITUATIONAL AWARENESS, DATA ANALYTICS AND ASSESSMENT (CYBER SA 2020) | 2020年

关键词：

Explainable AI; Smart healthcare; Personalised Connected Healthcare;

D O I：

10.1109/cybersa49311.2020.9139655

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Artificial Intelligence (AI) is an enabling technology that when integrated into healthcare applications and smart wearable devices such as Fitbits etc. can predict the occurrence of health conditions in users by capturing and analysing their health data. The integration of AI and smart wearable devices has a range of potential applications in the area of smart healthcare but there is a challenge in the black box operation of decisions made by AI models which have resulted in a lack of accountability and trust in the decisions made. Explainable AI (XAI) is a domain in which techniques are developed to explain predictions made by AI systems. In this paper, XAI is discussed as a technique that can used in the analysis and diagnosis of health data by AIbased systems and a proposed approach presented with the aim of achieving accountability. transparency, result tracing, and model improvement in the domain of healthcare.

引用

页数：2

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