The goal of this research is to correlate Raman spectra with tissue pathology using principal component analysis. Principal component analysis enables us to reduce our data set into a smaller number of mathematical lineshapes, called principal components, which represent the spectral variations in the data. A linear combination of these principal components can then be used to fit individual data. Finally, logisitic regression is used to correlate fitting coefficients with disease classifications and develop a diagnostic algorithm. So far, we have developed an initial decision algorithm and are in the process of testing it on data not included in the original data set.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
5P41RR002594-14
Application #
6121229
Study Section
Project Start
1999-06-01
Project End
2000-05-31
Budget Start
1998-10-01
Budget End
1999-09-30
Support Year
14
Fiscal Year
1999
Total Cost
Indirect Cost
Name
Massachusetts Institute of Technology
Department
Type
DUNS #
City
Cambridge
State
MA
Country
United States
Zip Code
02139
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