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Original Article

Prediction of intended career choice in family medicine using artificial neural networks

, &
Pages 63-69 | Received 30 Apr 2013, Accepted 25 May 2014, Published online: 16 Sep 2014

Figures & data

Table 1. Preference for family medicine in 316 final-year medical students.

Figure 1. Classification accuracy arising from adding the best item at each step of the SFS procedure (MLP with one hidden neuron, H = 1).
Figure 1. Classification accuracy arising from adding the best item at each step of the SFS procedure (MLP with one hidden neuron, H = 1).
Figure 2. Classification accuracy in MLP models of different complexity (regarding the number of hidden neurons H) when adding the first 20 items.
Figure 2. Classification accuracy in MLP models of different complexity (regarding the number of hidden neurons H) when adding the first 20 items.

Table 2. Twelve most important attitudes for discrimination between students regarding their preference for family medicine (analysed by SFS with ANNs, starting from a list of 164 attitudes, based on the European definition of family medicine and the EURACT Educational Agenda). The mean values and the standard deviations (SD) of both groups in the Likert scale are given in the second and in the third column.

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