Integrating classification and association rule mining B Liu, W Hsu, Y Ma Proceedings of the fourth international conference on knowledge discovery …, 1998 | 3609 | 1998 |
Development and validation of a deep learning system for diabetic retinopathy and related eye diseases using retinal images from multiethnic populations with diabetes DSW Ting, CYL Cheung, G Lim, GSW Tan, ND Quang, A Gan, H Hamzah, ... Jama 318 (22), 2211-2223, 2017 | 1991 | 2017 |
Mining association rules with multiple minimum supports B Liu, W Hsu, Y Ma Proceedings of the fifth ACM SIGKDD international conference on Knowledge …, 1999 | 1098 | 1999 |
Pruning and summarizing the discovered associations B Liu, W Hsu, Y Ma Proceedings of the fifth ACM SIGKDD international conference on Knowledge …, 1999 | 602 | 1999 |
Current research in the conceptual design of mechanical products W Hsu, IMY Woon Computer-Aided Design 30 (5), 377-389, 1998 | 443 | 1998 |
Analyzing the subjective interestingness of association rules B Liu, W Hsu, S Chen, Y Ma IEEE Intelligent Systems and their Applications 15 (5), 47-55, 2000 | 416 | 2000 |
A prime number labeling scheme for dynamic ordered XML trees X Wu, ML Lee, W Hsu Proceedings. 20th International Conference on Data Engineering, 66-78, 2004 | 352 | 2004 |
XClust: clustering XML schemas for effective integration ML Lee, LH Yang, W Hsu, X Yang Proceedings of the eleventh international conference on Information and …, 2002 | 348 | 2002 |
Using General Impressions to Analyze Discovered Classification Rules. B Liu, W Hsu, S Chen KDD, 31-36, 1997 | 338 | 1997 |
An integrated color-spatial approach to content-based image retrieval W Hsu, ST Chua, HH Pung Proceedings of the third ACM international conference on Multimedia, 305-313, 1995 | 330 | 1995 |
Retinal vascular tortuosity, blood pressure, and cardiovascular risk factors CY Cheung, Y Zheng, W Hsu, ML Lee, QP Lau, P Mitchell, JJ Wang, ... Ophthalmology 118 (5), 812-818, 2011 | 316 | 2011 |
Supporting frequent updates in r-trees: A bottom-up approach ML Lee, W Hsu, CS Jensen, B Cui, KL Teo Proceedings 2003 VLDB Conference, 608-619, 2003 | 300 | 2003 |
Artificial intelligence using deep learning to screen for referable and vision-threatening diabetic retinopathy in Africa: a clinical validation study V Bellemo, ZW Lim, G Lim, QD Nguyen, Y Xie, MYT Yip, H Hamzah, J Ho, ... The Lancet Digital Health 1 (1), e35-e44, 2019 | 294 | 2019 |
An effective approach to detect lesions in color retinal images H Wang, W Hsu, KG Goh, ML Lee Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR …, 2000 | 292 | 2000 |
Quantitative and qualitative retinal microvascular characteristics and blood pressure CY Cheung, WT Tay, P Mitchell, JJ Wang, W Hsu, ML Lee, QP Lau, ... Journal of hypertension 29 (7), 1380-1391, 2011 | 265 | 2011 |
Post-analysis of learned rules B Liu, W Hsu AAAI/IAAI, Vol. 1, 828-834, 1996 | 254 | 1996 |
Image mining: Trends and developments W Hsu, ML Lee, J Zhang Journal of intelligent information systems 19, 7-23, 2002 | 252 | 2002 |
Finding interesting patterns using user expectations B Liu, W Hsu, LF Mun, HY Lee IEEE Transactions on Knowledge and Data Engineering 11 (6), 817-832, 1999 | 252 | 1999 |
The retinal vasculature as a fractal: methodology, reliability, and relationship to blood pressure G Liew, JJ Wang, N Cheung, YP Zhang, W Hsu, ML Lee, P Mitchell, ... Ophthalmology 115 (11), 1951-1956. e1, 2008 | 237 | 2008 |
Quantitative assessment of early diabetic retinopathy using fractal analysis N Cheung, KC Donaghue, G Liew, SL Rogers, JJ Wang, SW Lim, ... Diabetes care 32 (1), 106-110, 2009 | 227 | 2009 |