The long-term goals of this proposal are to develop a medical digital library, which will provide domain- and task-specific information to support patient care, medical research and education.
The specific aims of this proposal are to develop a system that organizes and identifies reputable domain-specific information sources; provide users with greater expressive query power and precision; extract knowledge from medical data to support value-, and similarity, and content- based cross- referencing; provide access to prospective teaching and research cases; and support user- and device-specific information retrieval. Current large-scale information systems are designed to support general queries and lack the ability to support domain specific information gathering, navigation, and presentation. As a result, users are often unable to obtain desired specific information within a well-defined subject area. In medicine, appropriate information can make the difference between a proper diagnosis and an incorrect one. Medical records, teaching files and literature are scattered amongst many different data sources. New methods to provide unified access are needed for user-oriented applications. We propose to develop the following innovative methods to remedy these problems: (1) Scenario-based proxies, enabling the gathering and filtering of information customized for users within a pre-defined domain; 92) Context-sensitive navigation and matching, providing approximately matching and similarity links when an exact match to a user's request is unavailable; and (3) User and device models for customization of retrieved information and result presentation. A digital file room will be constructed using these techniques to provide customized information for the user. A scenario-based proxy provides a well-define focused information web allowing for intelligent navigation specific to a given scenario. A laboratory test-bed will be developed to study and validate the proposed system. Based on the laboratory results a prototype system will be developed for a well-circumscribed population and its effectiveness will be evaluated.
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| Ardekani, Siamak; Kumar, Anand; Bartzokis, George et al. (2007) Exploratory voxel-based analysis of diffusion indices and hemispheric asymmetry in normal aging. Magn Reson Imaging 25:154-67 |
| Ardekani, Siamak; Selva, Luis; Sayre, James et al. (2006) Quantitative metrics for evaluating parallel acquisition techniques in diffusion tensor imaging at 3 Tesla. Invest Radiol 41:806-14 |
| Ardekani, Siamak; Sinha, Usha (2006) Statistical representation of mean diffusivity and fractional anisotropy brain maps of normal subjects. J Magn Reson Imaging 24:1243-51 |
| Ardekani, Siamak; Sinha, Usha (2005) Geometric distortion correction of high-resolution 3 T diffusion tensor brain images. Magn Reson Med 54:1163-71 |
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