The need for quantification of uncertainty in artificial intelligence for clinical data analysis: increasing the level of trust in the decision-making process

被引：14

作者：

Abdar, Moloud ^{[1
]}

Khosravi, Abbas ^{[1
]}

Islam, Sheikh Mohammed Shariful ^{[2
]}

Acharya, U. Rajendra ^{[3
,4
,5
]}

Vasilakos, Athanasios V. ^{[6
,7
]}

机构：

[1] Deakin Univ, Inst Intelligent Syst Res & Innovat, Geelong, Vic 3216, Australia

[2] Deakin Univ, Sch Exercise & Nutr Sci, Inst Phys Act & Nutr, Melbourne, Vic 3125, Australia

[3] Ngee Ann Polytech, Dept Elect & Comp Engn, Singapore 599489, Singapore

[4] Singapore Univ Social Sci, Sch Sci & Technol, Dept Biomed Engn, Singapore 599491, Singapore

[5] Asia Univ, Dept Biomed Informat & Med Engn, Taichung 41354, Taiwan

[6] Fuzhou Univ, Coll Math & Comp Sci, Fuzhou 350116, Peoples R China

[7] Univ Agder, Ctr AI Res, N-4879 Grinstad, Norway

来源：

IEEE SYSTEMS MAN AND CYBERNETICS MAGAZINE | 2022年 / 8卷 / 03期

基金：

澳大利亚研究理事会;

关键词：

DIAGNOSTIC ERRORS; BURDEN;

D O I：

10.1109/MSMC.2022.3150144

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Data handling - Decision making - Decision support systems - Information analysis - Uncertainty analysis

引用

页码：28 / 40

页数：13

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