Predicting glaucomatous progression with piecewise regression model from heterogeneous medical data

Kyosuke Tomoda, Kai Morino, Hiroshi Murata, Ryo Asaoka, Kenji Yamanishi

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

5 Citations (Scopus)

Abstract

This study aims to accurately predict glaucomatous visual-field loss from patient disease data. In general, medical data show two kinds of heterogeneity: 1) internal heterogeneity, in which the phase of disease progression changes in an individual patient's time series dataset; and 2) external heterogeneity, in which the trends of disease progression differ among patients. Although some previous methods have addressed the external heterogeneity, the internal heterogeneity has never been taken into account in predictions of glaucomatous progression. Here, we developed a novel framework for dealing with the two kinds of heterogeneity to predict glaucomatous progression using a piecewise linear regression (PLR) model. We empirically demonstrate that our method significantly improves the accuracy of predicting visual-field loss compared with existing methods, and can successfully treat the two kinds of heterogeneity often observed in medical data.

Original languageEnglish
Title of host publicationHEALTHINF 2016 - 9th International Conference on Health Informatics, Proceedings; Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016
EditorsHaim Azhari, Hesham Ali, Ana Fred, James Gilbert, Carolina Ruiz, Jan Sliwa, Carla Quintao, Hugo Gamboa
PublisherSciTePress
Pages93-104
Number of pages12
ISBN (Electronic)9789897581700
Publication statusPublished - 2016
Externally publishedYes
Event9th International Conference on Health Informatics, HEALTHINF 2016 - Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016 - Rome, Italy
Duration: Feb 21 2016Feb 23 2016

Publication series

NameHEALTHINF 2016 - 9th International Conference on Health Informatics, Proceedings; Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016

Conference

Conference9th International Conference on Health Informatics, HEALTHINF 2016 - Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016
CountryItaly
CityRome
Period2/21/162/23/16

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Electrical and Electronic Engineering

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