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

Phono-spectrographic analysis of heart murmur in children

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Competency Assessment

Assessment is an essential feature of the competency-based educational model because only by means of evaluation can we verify achievement of specified learning outcomes. This is especially important in the context of health professions education, where the competencies of interest impact the well-being of patients. Therefore, just as with planning the instructional component of a curriculum, development of an assessment system must start with the specification of desired learning outcomes in the form of knowledge, skills, and attitudes expected of trainees or practitioners in order to provide safe and effective patient care. Issues to consider when judging the quality of evaluation methods include the reliability of data generated by the assessment, validity of decisions based on test results, educational impact on individuals undergoing evaluation and other stakeholders, and the feasibility of implementing the assessment system. In addition to these criteria and the particular competencies to be evaluated, the choice of testing methods from among numerous available techniques should consider multiple dimensions, such as appropriate level of assessment, stage of learner development, and, very importantly, overall purpose and context of the assessment. Ultimately, no one method can assess all aspects of professional competence, but familiarity with strengths and limitations of various modalities can guide the development of appropriate assessment systems. Strengths of simulation-based methods for evaluative purposes include the ability to assess actual performance of psychomotor skills and demonstration of nontechnical professional competencies in environments that safely and authentically mirror real practice settings. In addition, the programmability of simulations permits on-demand testing of rare but important clinical situations and consistent presentation of evaluation problems to multiple examinees; this reproducibility becomes especially important when high-stakes decisions are contingent upon such assessments