This systematic review identified seven new technologies, including camera-based photoplethysmography, reflectance pulse oximetry, laser Doppler methods, capacitive sensors, piezoelectric sensors, electromyography and a digital stethoscope. Clinicians should be aware of several of these, which may become available for clinical use in the near future.

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Objective definition of audio characteristics of abnormal paediatric breath sounds was achieved using DS technology. We demonstrated superiority of our DS method compared to traditional auscultation for detection of wheeze. What is Known: • The audiological characteristics of abnormal breath sounds have been well-described in adult populations but not in children. • Inter-observer agreement for detection of pathological breath sounds using standard auscultation has been shown to be poor, but the clinical value of now easily available digital stethoscopes has not been sufficiently examined. What is New: • Digital stethoscopes can objectively define the nature of pathological breath sounds such as wheeze and crackles in children. • Paediatric wheeze was better detected by digital stethoscopes than by standard auscultation performed by an expert paediatric clinician.

Interest in rural practice is not fully reflected in location during or after vocational training. The beneficial effects of rural undergraduate exposure might be lost if internship and vocational training programs provide insufficient rural clinical experiences and curriculum content. Continuation of the rural pathway might be needed to maintain rural practice intent.

Aim: To explore, synthesise and discuss currently available digital stethoscopes (DS) and the evidence for their use in paediatric medicine.Methods: Systematic review and narrative synthesis of digital stethoscope use in paediatrics following searches of OVID Medline, Embase, Scopus, PubMed and Google Scholar databases.Results: Six digital stethoscope makes were identified to have been used in paediatric focused studies so far. A total of 25 studies of DS use in paediatrics were included. We discuss the use of digital stethoscope technology in current paediatric medicine, comment on the technical properties of the available devices, the effectiveness and limitations of this technology, and potential uses in the fields of paediatrics and neonatology, from telemedicine to computer-aided diagnostics. Conclusion: Further validation and testing of available DS devices is required. Comparisonstudies between different types of DS would be useful in identifying strengths and flaws of each DS as well as identifying clinical situations for which each may be most appropriately suited.

The majority of fully qualified Monash MBBS graduates practicing in rural communities have rural backgrounds. The rural-background effect diminished over time and may need continued support during training and full practice.

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Background Manual auscultation to detect abnormal breath sounds has poor inter-observer reliability. Digital stethoscopes with artificial intelligence (AI) could improve reliable detection of these sounds. We aimed to independently test the abilities of AI developed for this purpose. Methods One hundred and ninety two auscultation recordings collected from children using two different digital stethoscopes (Clinicloud™ and Littman™) were each tagged as containing wheezes, crackles or neither by a pediatric respiratory physician, based on audio playback and careful spectrogram and waveform analysis, with a subset validated by a blinded second clinician. These recordings were submitted for analysis by a blinded AI algorithm (StethoMe AI) specifically trained to detect pathologic pediatric breath sounds. Results With optimized AI detection thresholds, crackle detection positive percent agreement (PPA) was 0.95 and negative percent agreement (NPA) was 0.99 for Clinicloud recordings; for Littman-collected sounds PPA was 0.82 and NPA was 0.96. Wheeze detection PPA and NPA were 0.90 and 0.97 respectively (Clinicloud auscultation), with PPA 0.80 and NPA 0.95 for Littman recordings. Conclusions AI can detect crackles and wheeze with a reasonably high degree of accuracy from breath sounds obtained from different digital stethoscope devices, although some device-dependent differences do exist.