Artificial Intelligence in Respiratory Care: An Educational Review

Respiratory diseases such as chronic obstructive pulmonary disease (COPD), asthma, tuberculosis, and acute respiratory distress syndrome (ARDS) remain leading causes of morbidity and mortality worldwide. Traditional respiratory care faces challenges in early diagnosis, personalized treatment, efficient resource allocation, and optimal mechanical ventilation management. Artificial intelligence (AI) has emerged as a transformative tool, offering applications in diagnosis, monitoring, treatment optimization, critical care support, and automated ventilator control. This comprehensive review examines AI's role across the respiratory care continuum, from diagnostic imaging and spirometry interpretation to autonomous multiparameter ventilator adjustment during maintenance and weaning phases. The article highlights quantitative evidence of clinical impact, regulatory status, challenges including algorithmic bias and health equity concerns, implementation strategies, and detailed analysis of AI-driven mechanical ventilation systems. Case studies illustrate real-world outcomes with specific effect sizes. The discussion emphasizes both the promise and limitations of AI, preparing healthcare professionals and students to critically evaluate its role in clinical practice.