Abstract: Worrying is a cognitive process that focuses on potential future negative events, where the outcome is often uncertain. Worries can arise in chains with one worry leading to another, often without solution. This may give rise to an uncontrollable worrying that may be associated with psychiatric disorders such as anxiety and depression. The generation of progressively more negative chains of worries can lead to a catastrophic phenomenon of pathological worrying. In this article we show that catastrophic worrying can be simulated by using a cascade-correlation algorithm for artificial neural networks.

Carlos Pelta, “Pathological Worrying and Artificial Neural Networks” International Journal of Advanced Computer Science and Applications(IJACSA), 11(1), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110106

@article{Pelta2020,
title = {Pathological Worrying and Artificial Neural Networks},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110106},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110106},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {1},
author = {Carlos Pelta}
}