I. Koprinska et al., SLEEP CLASSIFICATION IN INFANTS BY DECISION TREE-BASED NEURAL NETWORKS, Artificial intelligence in medicine, 8(4), 1996, pp. 387-401
This paper presents an AI-based approach to automatic sleep stage scor
ing. The system TBNN (Tree-Based Neural Network) uses a decision-tree
generator to provide knowledge that defines the architecture of a back
propagation neural network, including feature selection and initialisa
tion of the weights. The case study reports a successful application t
o the data from polygraphic all-night sleep of 8 babies aged 6 months.
The teaching input was provided by a medical expert in accordance wit
h the rules of Guilleminault and Souquet. The performance of TBNN is c
ompared with 5 other methods and the results are discussed.