Data mining: concepts and techniques
Data mining: concepts and techniques
Mathematics and Physics of Emerging Biomedical Imaging
Mathematics and Physics of Emerging Biomedical Imaging
Data Mining Using SAS Applications
Data Mining Using SAS Applications
Guest editorial: human-centered computing in health information systems. Part 1: Analysis and design
Journal of Biomedical Informatics - Special issue: Human-centered computing in health information systems. Part 1: Analysis and design
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Objective: The general concept surrounding fMRI data analysis for decision support is leveraging previously hidden knowledge from publicly available metadata sources with a high degree of precision. Methods and materials: Normalized fMRI scans are used to calculate cumulative voxel intensity curves for every subject in the dataset that fits chosen demographic criteria. The voxel intensity curve has a direct linear relationship to the subject's neuronal activity. In the case of head trauma, a subject's voxel intensity curve would be statistically compared to the weighted average curve for every subject in dataset that is demographically similar. If the new subject's neuronal activity falls below the threshold for their demographic group, the brain injury detection (BID) system would then pinpoint the areas of deficiency based on Broadmann's cortical areas. Analysis: The analysis presented in this paper indicates that statistical differences among demographic groups exist in BOLD fMRI responses. Conclusion: Useful knowledge can in fact be leveraged from mining stockpiled fMRI data without the need for unique human identifiers. The BID system offers the radiologist a statistically based decision support for brain injury.