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Autonomous, Decentralized and Privacy-Enabled Data Preparation for Evidence-Based Medicine with Brain Aneurysm as a Phenotype
Khalid Mahmood MALIK Hisham KANAAN Vian SABEEH Ghaus MALIK
IEICE TRANSACTIONS on Communications
Publication Date: 2018/08/01
Online ISSN: 1745-1345
Type of Manuscript: Special Section PAPER (Special Section on Autonomous Decentralized Systems Technologies and Approaches Innovation through Structure Change of Society and Life)
semantic web, autonomous decentralized system, semantic similarity, brain aneurysm, privacy, clinical notes,
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To enable the vision of precision medicine, evidence-based medicine is the key element. Understanding the natural history of complex diseases like brain aneurysm and particularly investigating the evidences of its rupture risk factors relies on the existence of semantic-enabled data preparation technology to conduct clinical trials, survival analysis and outcome prediction. For personalized medicine in the field of neurological diseases, it is very important that multiple health organizations coordinate and cooperate to conduct evidence based observational studies. Without the means of automating the process of privacy and semantic-enabled data preparation to conduct observational studies at intra-organizational level would require months to manually prepare the data. Therefore, this paper proposes a semantic and privacy enabled, multi-party data preparation architecture and a four-tiered semantic similarity algorithm. Evaluation shows that proposed algorithm achieves a precision of 79%, high recall at 83% and F-measure of 81%.