Stability-weighted matrix completion of incomplete multi-modal data for disease diagnosis

Kim Han Thung, Ehsan Adeli, Pew Thian Yap, Dinggang Shen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

Effective utilization of heterogeneous multi-modal data for Alzheimer’s Disease (AD) diagnosis and prognosis has always been hampered by incomplete data. One method to deal with this is low-rank matrix completion (LRMC),which simultaneous imputes missing data features and target values of interest. Although LRMC yields reasonable results,it implicitly weights features from all the modalities equally,ignoring the differences in discriminative power of features from different modalities. In this paper,we propose stability-weighted LRMC (swLRMC),an LRMC improvement that weights features and modalities according to their importance and reliability. We introduce a method,called stability weighting,to utilize subsampling techniques and outcomes from a range of hyper-parameters of sparse feature learning to obtain a stable set of weights. Incorporating these weights into LRMC,swLRMC can better account for differences in features and modalities for improving diagnosis. Experimental results confirm that the proposed method outperforms the conventional LRMC,feature-selection based LRMC,and other state-of-the-art methods.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings
PublisherSpringer Verlag
Pages88-96
Number of pages9
Volume9901 LNCS
ISBN (Print)9783319467221
DOIs
Publication statusPublished - 2016
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9901 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Fingerprint

Matrix Completion
Low-rank Matrices
Stiffness matrix
Modality
Subsampling
Alzheimer's Disease
Hyperparameters
Stable Set
Incomplete Data
Prognosis
Missing Data
Feature Selection
Weighting
Feature extraction
Target
Experimental Results

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Thung, K. H., Adeli, E., Yap, P. T., & Shen, D. (2016). Stability-weighted matrix completion of incomplete multi-modal data for disease diagnosis. In Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings (Vol. 9901 LNCS, pp. 88-96). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9901 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-46723-8_11

Stability-weighted matrix completion of incomplete multi-modal data for disease diagnosis. / Thung, Kim Han; Adeli, Ehsan; Yap, Pew Thian; Shen, Dinggang.

Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. Vol. 9901 LNCS Springer Verlag, 2016. p. 88-96 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9901 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Thung, KH, Adeli, E, Yap, PT & Shen, D 2016, Stability-weighted matrix completion of incomplete multi-modal data for disease diagnosis. in Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. vol. 9901 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9901 LNCS, Springer Verlag, pp. 88-96. https://doi.org/10.1007/978-3-319-46723-8_11
Thung KH, Adeli E, Yap PT, Shen D. Stability-weighted matrix completion of incomplete multi-modal data for disease diagnosis. In Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. Vol. 9901 LNCS. Springer Verlag. 2016. p. 88-96. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-46723-8_11
Thung, Kim Han ; Adeli, Ehsan ; Yap, Pew Thian ; Shen, Dinggang. / Stability-weighted matrix completion of incomplete multi-modal data for disease diagnosis. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. Vol. 9901 LNCS Springer Verlag, 2016. pp. 88-96 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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