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Developing a Low Dimensional Patient Class Profile in Accordance to Their Respiration-Induced Tumor Motion

Summary: Develops low-dimensional class profiles for respiration-induced tumor motion. Adaptive segmentation yields multi-sets of segments around baseline, ES- and D-Range shifts; a modified multi-set clustering builds clinically interpretable profiles. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11444
Venue
VLDB
Year
2017
Pagerank
4.1945683e-05
Overall Rank
11,801 | 17.91%
DOI
-

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

Rank Cited Paper Year Venue Pagerank
1,157 A Data-adaptive and Dynamic Segmentation Index for Whole Matching on Time Series 2013 VLDB 0.00013610658
5,830 GEMINI: An Integrative Healthcare Analytics System 2014 VLDB 5.3113542e-05
6,918 Aggregate Profile Clustering for Telco Analytics 2013 VLDB 4.8925595e-05
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