Stethoscopes have been used to guide clinicians during the resuscitation process and accurate diagnosis of the breathing sound is important to ensure successful procedures. It is challenging to make accurate diagnosis to neonates’ breathing sounds because (i) the neonate breathing sound is very soft and hardly detectable by non-specialists, especially in the wards surrounded by constantly beeping of monitors, and (ii) it requires experience to identify the subtle difference in the neonates’ breathing sounds.Manual diagnosis of air entry in neonates requires skill and experience in the clinician and is subjected to error. Here, we proposed to develop an AI-integrated framework to analyse the neonates’ breathing sound that can guide clinicians during the resuscitation process. The system will be able to interpret and make reliable recommendations to aid clinicians in the differential diagnosis of the condition of the neonates, especially if this was accompanied by deterioration of the vital signs of the infant.

Inadequate delivery of resuscitation of the infant may cause inadvertent death. Lung auscultation, the main modality used by clinicians to adequately assess breath sounds using stethoscope following infant resuscitation is fraught with difficulties, as its function is restricted with dependence on clinician’s interpretive skills. There is thus an urgent need to innovate a novel stand-alone low-cost stethoscope amplifier with embedded optimized artificial intelligence (AI) algorithm for robust assessment during cardiopulmonary resuscitation/intubation of infants. This project will provide the respiratory sounds data for the purpose of creating a repository of paediatric breath sounds and for the purpose of development of this device (StethoKord.Think.Rescue). The data will be validated against the patient’s diagnoses and radiographic images. The outcomes of the project will aid in effective cardiopulmonary resuscitation, especially in resource-limited countries, facilitate examination of a potentially infectious infants’ patient while clinicians are in PPE,and foster education of medical students and healthcare workers.