Best Clinical AI Tools for Pulmonology & Critical Care

Critical care medicine generates more data per patient-hour than any other specialty. A mechanically ventilated patient in the ICU has continuous monitoring of respiratory mechanics (tidal volume, plateau pressure, driving pressure, compliance), hemodynamics (arterial line, CVP, sometimes pulmonary artery catheter), and laboratory values updated multiple times per day. Managing this data stream requires systematic protocols — and the evidence base for critical care evolves rapidly. The ARDSNet low tidal volume ventilation protocol, published in 2000, fundamentally changed ICU care and remains the foundation of lung-protective ventilation. But subsequent trials have added layers of complexity: prone positioning (PROSEVA trial), neuromuscular blockade (ACURASYS and ROSE trials), ECMO criteria (EOLIA trial), and high-flow nasal cannula thresholds (FLORALI trial). CDS tools that integrate these protocols and help clinicians navigate the branching decision trees of mechanical ventilation score highest in our ICU evaluation. Outpatient pulmonology presents different CDS challenges. COPD management has grown increasingly complex with the 2023 GOLD report recommending a stepwise approach based on exacerbation history, blood eosinophil count, and symptom burden — driving selection among LAMA, LABA, ICS, and now biologics. Asthma management follows a similar trajectory, with biologic therapies (omalizumab, mepolizumab, dupilumab, tezepelumab) requiring specific biomarker criteria for selection. Interstitial lung disease classification involves pattern recognition across dozens of entities with overlapping HRCT findings.