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  • Kwon, Bum ChulIBM Research Cambridge (author)

DPVis : Visual Analytics with Hidden Markov Models for Disease Progression Pathways

  • Article/chapterEnglish2021

Publisher, publication year, extent ...

  • 2021
  • 16 s.

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  • LIBRIS-ID:oai:lup.lub.lu.se:b4778f5a-00e3-49b5-aa81-f54f9e89806c
  • https://lup.lub.lu.se/record/b4778f5a-00e3-49b5-aa81-f54f9e89806cURI
  • https://doi.org/10.1109/TVCG.2020.2985689DOI

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  • Language:English
  • Summary in:English

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  • Subject category:art swepub-publicationtype
  • Subject category:ref swepub-contenttype

Notes

  • Clinical researchers use disease progression models to understand patient status and characterize progression patterns from longitudinal health records. One approach for disease progression modeling is to describe patient status using a small number of states that represent distinctive distributions over a set of observed measures. Hidden Markov models (HMMs) and its variants are a class of models that both discover these states and make inferences of health states for patients. Despite the advantages of using the algorithms for discovering interesting patterns, it still remains challenging for medical experts to interpret model outputs, understand complex modeling parameters, and clinically make sense of the patterns. To tackle these problems, we conducted a design study with clinical scientists, statisticians, and visualization experts, with the goal to investigate disease progression pathways of chronic diseases, namely type 1 diabetes (T1D), Huntington's disease, Parkinson's disease, and chronic obstructive pulmonary disease (COPD). As a result, we introduce DPVis which seamlessly integrates model parameters and outcomes of HMMs into interpretable and interactive visualizations. In this study, we demonstrate that DPVis is successful in evaluating disease progression models, visually summarizing disease states, interactively exploring disease progression patterns, and building, analyzing, and comparing clinically relevant patient subgroups.

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  • Anand, VibhaIBM Research (author)
  • Severson, Kristen A.IBM Research (author)
  • Ghosh, SoumyaIBM Thomas J. Watson Research Center (author)
  • Sun, ZhaonanIBM Research (author)
  • Frohnert, Brigitte I.University of Colorado (author)
  • Lundgren, MarkusLund University,Lunds universitet,Institutionen för kliniska vetenskaper, Malmö,Medicinska fakulteten,Department of Clinical Sciences, Malmö,Faculty of Medicine(Swepub:lu)med-mn2 (author)
  • Ng, KenneyIBM Thomas J. Watson Research Center (author)
  • IBM Research CambridgeIBM Research (creator_code:org_t)

Related titles

  • In:IEEE Transactions on Visualization and Computer Graphics27:9, s. 3685-37001077-2626

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Kwon, Bum Chul
Anand, Vibha
Severson, Kriste ...
Ghosh, Soumya
Sun, Zhaonan
Frohnert, Brigit ...
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Lundgren, Markus
Ng, Kenney
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MEDICAL AND HEALTH SCIENCES
MEDICAL AND HEAL ...
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and Biomedical Labor ...
MEDICAL AND HEALTH SCIENCES
MEDICAL AND HEAL ...
and Clinical Medicin ...
and General Practice
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