This desktop program allows for exporting the audio files in “.wav” format only using the three aforementioned filters. The data files were extracted from the on-board memory of the stethoscope using the 3M™Littmann® stethassist visualization software. Table 2 shows the chest zones included in the dataset and the corresponding number of subjects. Lower zone: located in the region enclosed by the inferior aspect of the hilum and the hemidiaphragm. Figure 1 shows a sample of the three filters along with the spectrogram. The letter E is used with extended mode filtration, which amplifies sounds in the frequency range Hz, but emphasizes the frequency sounds in the range Hz. The letter D is used with Diaphragm mode filtration, which amplifies sounds in the frequency range Hz, but emphasizes the frequency sounds in the range Hz. The letter B is used with Bell mode filtration, which amplifies sounds in the frequency range Hz, but emphasizes the low frequency sounds in the range Hz. Three types of filters were included in the data. After that, the file name includes the diagnosis, type of sound, location of measurement on chest, subject’s age, and subject’s gender. This is followed by the letter P, a unique sequential patient number starting from 1, and an underscore. The name of each data file starts with the type of filter encoded as letter B, D, or E. The number of extractable respiratory cycles for each health condition was reported elsewhere. There were no min duration requirements imposed on the physician examining the subjects. The max duration is limited by recording capabilities of the electronic stethoscope. The duration of each recording ranges from 5 to 30 seconds, which is enough to cover at least one respiratory cycle. Unlike relevant datasets, the dataset contains one recording per subject. Alkhodari, Automatic identification of respiratory diseases from stethoscopic lung sound signals using ensemble classifiers, Biocybernetics and Biomedical Engineering. The stored data does not contain any reference to participants.

However, the doi will become active and the data will be published upon the acceptance of this article (i.e., embargo will be removed). You may need to create a Mendeley account to login.

Repository name: Mendeley Data Data identification number: Direct URL to data: Instructions for accessing these data: Use the direct link to access the data. Institution: King Abdullah University Hospital City/Town/Region: Ramtha/Irbid Country: Jordan This software allows for exporting files using three filters (Bell, diaphragm, and extended), which emphasizes different sound frequencies corresponding to the sounds from specific organs (e.g., heart or lung). The 3M™Littmann® heart and lung sound visualization software was used to extract the recordings from the stethoscope. The collection process did not attempt to record heart sounds. The data was recorded with the aim of diagnosing the suspected pulmonary disease from the lung sound. The recording was performed using the 3M™Littmann® Electronic Stethoscope model 3200, and transmitted to a computer using the provided Bluetooth adaptor. Lung sounds were acquired using an electronic stethoscope placed on various vantage points of the chest wall. Machine Learning Pulmonary diseases clinical application

Lung sounds placement