Disease pattern recognition in infrared spectra of human sera with diabetes mellitus as an example

To benefit from the full information content of the mid-IR spectra of human sera, we directly related the overall shape of the spectra to the donors' disease states. For this approach of disease pattern recognition we applied cluster analysis and discriminant analysis to the example of the disease s tates diabetes type 1, diabetes type 2, and healthy. In a binary, supervise d classification of any pair of these disease states we achieved specificit ies and sensitivities of similar to 80% within our data set. (C) 2000 Optic al Society of America OCIS codes: 070.5010, 170.1470, 170.1580, 170.1610, 1 70.4580, 300.6390.