Evaluation of standard and semantically-augmented distance metrics for neurology patients.

Background: Patient distances can be calculated based on signs and symptoms derived from an ontological hierarchy. There is controversy as to whether patient distance metrics that consider the semantic similarity between concepts can outperform standard patient distance metrics that are agnostic to concept similarity. The choice of distance metric can dominate the performance of classification or clustering algorithms.

A Neuro-ontology for the neurological examination.

Background: The use of clinical data in electronic health records for machine-learning or data analytics depends on the conversion of free text into machine-readable codes. We have examined the feasibility of capturing the neurological examination as machine-readable codes based on UMLS Metathesaurus concepts.

Methods: We created a target ontology for capturing the neurological examination using 1100 concepts from the UMLS Metathesaurus.

Making the neurology clerkship more effective: can e-Textbook facilitate learning?

Objective: In 1998, the 4-week neurology elective clerkship was converted into a 2-week required neurology rotation at the University of Illinois at Chicago. We hypothesized that the interactive e-Textbook, a computer-assisted learning tool, could successfully replace a paper-based syllabus and a traditional neurology textbook during a 2-week rotation, while incorporating department teaching conferences to replace the medical student lecture series.

Methods: We created an e-Textbook and made it available simultaneously in a CD-ROM format and on a password-protected website.

17O magnetic resonance imaging of the human brain.

Here we show the first example of in vivo oxygen-17 (17O) magnetic resonance imaging of the human in natural abundance. Two-dimensional fast multi-planar gradient recalled 90 deg echo (FMPGR/90) pulse sequence and three-dimensional projection reconstruction pulse sequence methods were used.