Image Mining in IRIS: Integrated Retinal Information System

Summary: IRIS integrates retinal image analysis with a unified diabetic patient database for screening, trend, and progression tracking. Demonstrates data-management-oriented image mining: feature extraction from retinal images and a classifier for tortuosity in retinal vessels. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 3305
Venue: SIGMOD
Year: 2000
Pagerank: -
Overall Rank: 14,091 | 3.33%
DOI: 10.1145/342009.336573

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

1. Wynne Hsu (National University of Singapore)
2. Mong Li Lee (National University of Singapore)
3. Kheng Guan Goh (National University of Singapore)

BibTeX Citation

@inproceedings{hsu_sigmod00,
        title = {{Image Mining in IRIS: Integrated Retinal Information System}},
        author = {Hsu, Wynne and Lee, Mong Li and Goh, Kheng Guan},
        series = {{SIGMOD} '00},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/342009.336573},
        url = {https://dl.acm.org/doi/10.1145/342009.336573},
        year = {2000}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
13,990	Advanced Database Technologies in a Diabetic Healthcare System	2002	VLDB	-

Outgoing Citations (Sorted by Pagerank)

Showing 0 of 0 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank

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