BACKGROUND AND RELATED WORK
The diagnosis of disease can be viewed as a classification
task that sorts subjects into two classes: those with disease
and those without it. Machine learning methods and, in
Manuscript received April 23, 2010. This work was supported in part by
the National Science Foundation Graduate Research Fellowship Program.
I. Tien and S. D. Glaser are with the Center for Information Technology
Research in the Interest of Society (CITRIS), University of California,
Berkeley, CA 94720 USA (emails: itien@berkeley.edu and
glaser@berkeley.edu).
M. J. Aminoff is with the Neurology Department, University of
California, San Francisco, CA 94143 USA (email:
aminoffm@neurology.ucsf.edu).
BACKGROUND AND RELATED WORKThe diagnosis of disease can be viewed as a classificationtask that sorts subjects into two classes: those with diseaseand those without it. Machine learning methods and, inManuscript received April 23, 2010. This work was supported in part bythe National Science Foundation Graduate Research Fellowship Program.I. Tien and S. D. Glaser are with the Center for Information TechnologyResearch in the Interest of Society (CITRIS), University of California,Berkeley, CA 94720 USA (emails: itien@berkeley.edu andglaser@berkeley.edu).M. J. Aminoff is with the Neurology Department, University ofCalifornia, San Francisco, CA 94143 USA (email:aminoffm@neurology.ucsf.edu).
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