| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 10320509 | Artificial Intelligence in Medicine | 2015 | 9 Pages |
Abstract
A practical method for predicting probability for antimicrobial susceptibility could be developed based on a semi-naïve Bayesian approach using statistical data on cross-susceptibilities and cross-resistances. The reduction in Brier distance from 37.7% to 25.3%, indicates a significant advantage to the proposed min2max2 method (p < 10 99).
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Steen Andreassen, Alina Zalounina, Mical Paul, Line Sanden, Leonard Leibovici,