White Learning: A White-Box Data Fusion Machine Learning Framework for Extreme and Fast Automated Cancer Diagnosis

doi:10.1109/MITP.2019.2931415

UM > Faculty of Science and Technology > DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE

Residential College	false
Status	已發表Published
	White Learning: A White-Box Data Fusion Machine Learning Framework for Extreme and Fast Automated Cancer Diagnosis
	Tengyue Li1 ; Simon Fong1 ; Lian-Sheng Liu 2; Xin-She Yang 3; Xingshi He 4; Jinan Fiaidhi 5; Sabah Mohammed 5
	2019-09-11
Source Publication	IT Professional
ISSN	1520-9202
Volume	21 Issue:5 Pages:71-77
DOI	10.1109/MITP.2019.2931415
URL	View the original
Indexed By	SCIE
Language	英語English
WOS Research Area	Computer Science ; Telecommunications
WOS Subject	Computer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS ID	WOS:000485735800013
Publisher	IEEE COMPUTER SOC, 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314 USA
Scopus ID	2-s2.0-85072240913
Fulltext Access	View Full-Text via DOI View Full-Text via Web of Science View Full-Text via Scopus
Citation statistics
Document Type	Journal article
Collection	DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation	1.University of Macau 2.Hospital of Guangzhou,University of TCM, China 3.Middlesex University 4.Xi'An Polytechnic University 5.Lakehead University
First Author Affilication	University of Macau
Recommended Citation GB/T 7714	Tengyue Li,Simon Fong,Lian-Sheng Liu,et al. White Learning: A White-Box Data Fusion Machine Learning Framework for Extreme and Fast Automated Cancer Diagnosis[J]. IT Professional, 2019, 21(5), 71-77.
APA	Tengyue Li., Simon Fong., Lian-Sheng Liu., Xin-She Yang., Xingshi He., Jinan Fiaidhi., & Sabah Mohammed (2019). White Learning: A White-Box Data Fusion Machine Learning Framework for Extreme and Fast Automated Cancer Diagnosis. IT Professional, 21(5), 71-77.
MLA	Tengyue Li,et al."White Learning: A White-Box Data Fusion Machine Learning Framework for Extreme and Fast Automated Cancer Diagnosis".IT Professional 21.5(2019):71-77.

Files in This Item:
There are no files associated with this item.

If you have any objections to this item, please fill out the form below and the administrator will contact you as soon as possible.
Content:
Email：	*
Affiliation No.
Verification Code:	Refresh

Any comments and suggestions are welcomed.
Title:	*
Content:
Email：	*
Verification Code:	Refresh