Pattern search in multi-structure data: a framework for the next-generation evidence-based medicine

Sreenivas R. Sukumar; Keela C. Ainsworth

doi:10.1117/12.2044378

19 March 2014 Pattern search in multi-structure data: a framework for the next-generation evidence-based medicine

Sreenivas R. Sukumar, Keela C. Ainsworth

Proceedings Volume 9039, Medical Imaging 2014: PACS and Imaging Informatics: Next Generation and Innovations; 90390O (2014) https://doi.org/10.1117/12.2044378
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

With the impetus towards personalized and evidence-based medicine, the need for a framework to analyze/interpret quantitative measurements (blood work, toxicology, etc.) with qualitative descriptions (specialist reports after reading images, bio-medical knowledgebase, etc.) to predict diagnostic risks is fast emerging. Addressing this need, we pose and answer the following questions: (i) How can we jointly analyze and explore measurement data in context with qualitative domain knowledge? (ii) How can we search and hypothesize patterns (not known apriori) from such multi-structure data? (iii) How can we build predictive models by integrating weakly-associated multi-relational multi-structure data? We propose a framework towards answering these questions. We describe a software solution that leverages hardware for scalable in-memory analytics and applies next-generation semantic query tools on medical data.

Citation Download Citation

Sreenivas R. Sukumar and Keela C. Ainsworth "Pattern search in multi-structure data: a framework for the next-generation evidence-based medicine", Proc. SPIE 9039, Medical Imaging 2014: PACS and Imaging Informatics: Next Generation and Innovations, 90390O (19 March 2014); https://doi.org/10.1117/12.2044378

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