RESULTS:
A higher prevalence of potential risk factors was observed in twenty-two and fifteen factors in external control and internal control group respectively. For six of them, the difference in prevalence was statistically significant. Specialized Artificial Neural Networks (ANNs) discriminated between autism and control subjects with 80.19% global accuracy when the data set was pre-processed with TWIST system selecting 16 out of 27 variables. Logistic regression applied to 27 variables gave unsatisfactory results with global accuracy of 46%.