Phono-spectrographic analysis of heart murmur in children

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Intelligent Identification of Childhood Musical Murmurs

Heart murmurs are often the first signs of heart valvular disorders. However, most heart murmurs detected in children are innocent musical murmurs (also called Still's murmurs), which should be distinguished from other murmur types that are mostly pathological, such as regurgitant, obstructive, and flow murmurs. In order to reduce both unnecessary healthcare expenditures and parental anxiety, this study aims to develop algorithms for intelligently identifying musical murmurs in children. Discrete wavelet transform was applied to phonocardiographic signals to extract features. Singular value decomposition was applied on the matrix derived from continuous wavelet transform to extract extra features. The sequential forward feature selection algorithm was then utilized to select significant features. Musical murmurs were subsequently differentiated via a classification procedure consisting of three classification techniques: discriminant analysis, support vector machine, and artificial neural network. The results of 89.02% sensitivity, 84.76% specificity and 87.36% classification accuracy were achieved

La téléxérographie du crâne : étude clinique et radiologique

Les auteurs démontrent, sur 70 clichés comparatifs, la supériorité de la téléxérographie pour la céphalométrie orthodontique ou chirurgicale. Le squelette et les tissus mous sont toujours également lisibles sur le même cliché dont la réalisation technique est simple. L'irradiation nécessaire a été mesurée. Elle est actuellement un peu plus élevée en xérographie, mais devrait être inférieure à l'avenir