India, Dec. 1 -- Diagnosis of lung diseases has progressed from the use of hearing of chest sounds with ears to the applications of artificial intelligence (AI) algorithms integrated with digital stethoscopes. AI algorithms analyse vast data sets, including clinical and genetic information, to identify a disease. In respiratory medicine, AI can be used to find the aetiological basis of breathlessness as well as to predict patient outcomes by analysing changes over time from serial HRCT scans and lung functions tests, for example in patients with interstitial lung disease. There are, however, many challenges and pitfalls in the AI interpretation. Most AI models are based on data sets from single centres. Their accuracy may decline significantly when applied to patients from different geographic, socioeconomic, or demographic backgrounds, which indicate a patient's likely response to specific treatments. AI also allows clinicians to create personalised treatment plans, thus enhancing therapeutic effectiveness. The AI-assisted method reduces diagnostic uncertainty, minimises the need for invasive procedures, and helps in delivering more precise and personalised patient care. The author of this article is an MBBS, DNB, DM Pulmonary and Critical Care Medicine (PGIMER Chandigarh), FCCP, consultant pulmonologist at Jindal Clinics, Centre for Interventional Pulmonology and Sleep Medicine, SCO 21, Sector 20-D, Chandigarh, who can be contacted at 958-246-9429...