Development of a pediatric cardiac computer aided auscultation decision support system.

Developing countries have a large population of children living with undiagnosed heart murmurs. As a result of an accompanying skills shortage, most of these children will not get the necessary treatment. The objective of this paper was to develop a decision support system. This could enable health care providers in developing countries with tools to screen large amounts of children without the need for expensive equipment or specialist skills. For this purpose an algorithm was designed and tested to detect heart murmurs in digitally recorded signals. A specificity of 94% and a sensitivity of 91% were achieved using novel signal processing techniques and an ensemble of neural networks as classifier.