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(Circulation. 2001;103:2711.)
© 2001 American Heart Association, Inc.

Clinical Investigation and Reports

Artificial Neural Network–Based Method of Screening Heart Murmurs in Children

Curt G. DeGroff, MD; Sanjay Bhatikar, PhD; Jean Hertzberg, PhD; Robin Shandas, PhD; Lilliam Valdes-Cruz, MD; Roop L. Mahajan, PhD

From the University of Colorado Health Sciences Center, the Children’s Hospital, Denver (C.G.D., R.S., L.V-C.), and the Department of Mechanical Engineering, University of Colorado, Boulder (S.B., J.H., R.S., R.L.M.), Colo.

Correspondence to Curt G. DeGroff, MD, University of Colorado Health Science Center, the Children’s Hospital, 1056 E 19th Ave, B-100 Denver, CO 80218. E-mail degroff.curt{at}tchden.org

Background—Early recognition of heart disease is an important goal in pediatrics. Efforts in developing an inexpensive screening device that can assist in the differentiation between innocent and pathological heart murmurs have met with limited success. Artificial neural networks (ANNs) are valuable tools used in complex pattern recognition and classification tasks. The aim of the present study was to train an ANN to distinguish between innocent and pathological murmurs effectively.

Methods and Results—Using an electronic stethoscope, heart sounds were recorded from 69 patients (37 pathological and 32 innocent murmurs). Sound samples were processed using digital signal analysis and fed into a custom ANN. With optimal settings, sensitivities and specificities of 100% were obtained on the data collected with the ANN classification system developed. For future unknowns, our results suggest the generalization would improve with better representation of all classes in the training data.

Conclusion—We demonstrated that ANNs show significant potential in their use as an accurate diagnostic tool for the classification of heart sound data into innocent and pathological classes. This technology offers great promise for the development of a device for high-volume screening of children for heart disease.

Key Words: heart murmurs • neural networks (computer) • child • heart defects, congenital

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