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Stethoscope placement for lung sounds3/21/2024 Improved music genre classification with convolutional neural networks pp. Impact of slow breathing on the blood pressure and subarachnoid space width oscillations in humans. Nuckowska M.K., Gruszecki M., Kot J., Wolf J., Guminski W., Frydrychowski A.F., Wtorek J., Narkiewicz K., Winklewski P.J. Precision Medicine Powered by pHealth and Connected Health. In: Maglaveras N., Chouvarda I., de Carvalho P., editors. α respiratory sound database for the development of automated classification. Rocha B.M., Filos D., Mendes L., Vogiatzis I., Perantoni E., Kaimakamis E., Natsiavas P., Oliveira A., Jácome C., Marques A., Paiva R.P., Chouvarda I., Carvalho P., Maglaveras N. Ibnian, A dataset of lung sounds recorded from the chest wall using an electronic stethoscope, 2021, URL. The same methods can also be applied to the study of heart sounds.Īrtificial intelligence Deep learning Electronic stethoscope Lung sounds Pulmonary diseases. The dataset can be used for the development of automated methods that detect pulmonary diseases from lung sounds or identify the correct type of lung sound. Each recording was replicated three times corresponding to various frequency filters that emphasize certain bodily sounds. The stethoscope placement on the subject was determined by the specialist physician performing the diagnosis. The dataset presented in this article contains the audio recordings from the examination of the chest wall at various vantage points. The dataset includes sounds from seven ailments (i.e., asthma, heart failure, pneumonia, bronchitis, pleural effusion, lung fibrosis, and chronic obstructive pulmonary disease (COPD)) as well as normal breathing sounds. We used an electronic stethoscope to record lung sounds from healthy and unhealthy subjects. The advancement of stethoscope technology has enabled high quality recording of patient sounds.
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