Abstract
A sequential method of pattern recognition was used to recognize hyperthyroidism in a sample of 2219 patients being treated at the Straub Clinic in Honolulu. For this, the method of Class Featuring Information Compression (CLAFIC) was used, introducing some significant improvements in computer medical diagnosis, which, by its very nature is a pattern recognition problem. A unique subspace characterizes each class at every decision stage, and the most prominent class features are selected. Thus, the symptoms which best distinguish hyperthyroidism are extracted at every step and the number of tests required to reach a diagnosis is reduced.
| Original language | American English |
|---|---|
| Pages | 198-206 |
| Number of pages | 9 |
| State | Published - 1969 |
| Externally published | Yes |
| Event | IEEE, Syst Sci & Cybern Conf Rec - Philadelphia, PA, USA Duration: Oct 22 1969 → Oct 24 1969 |
Other
| Other | IEEE, Syst Sci & Cybern Conf Rec |
|---|---|
| City | Philadelphia, PA, USA |
| Period | 10/22/69 → 10/24/69 |
ASJC Scopus subject areas
- General Engineering