Lung auscultation - today and tomorrow- a narrative review

Lung auscultation is a fundamental diagnostic tool for respiratory conditions. Despite advancements in medical technology, the analogue stethoscope remains a crucial tool for diagnosing pulmonary diseases. However, traditional auscultation methods have limitations, including variability in sound interpretation and examiner dependency.

This review explores the current standards of lung auscultation, highlighting the challenges and limitations of traditional methods. Further, it examines the potential of digital stethoscopes and artificial intelligence (AI) in enhancing the accuracy and reliability of lung sound analysis. A broad and iterative exploration of the literature was conducted, mainly using PubMed, Scopus, and Google Scholar.

The advent of digital stethoscopes and AI presents a potential for more standardized lung auscultation. Although challenging, these technologies can standardize sound categorization, improve diagnostic accuracy, and facilitate remote consultations. There will be a need for large data sets with high quality sound files and outcome measures, and noise during recording needs to be handled. The integration of digital lung auscultation with telemedicine platforms could significantly improve patient monitoring and care, particularly for those with chronic respiratory conditions.