Artificial Intelligence and Precision Medicine in Respiratory and Critical Care: From Data-Driven Diagnostics to Clinical Translation

Rapid advances in artificial intelligence (AI), computational medicine, and digital health are fundamentally reshaping respiratory and critical care medicine. Machine learning algorithms, natural language processing, and AI-enhanced imaging systems are increasingly demonstrating strong potential to improve early diagnosis, risk stratification, and individualized patient management.

In parallel, progress in genomics, proteomics, metabolomics, and other multi-omics technologies has significantly expanded the scope of precision medicine in diseases such as tuberculosis, asthma, chronic obstructive pulmonary disease (COPD), interstitial lung diseases (ILD), and acute respiratory failure. Despite these advances, the translation of AI and precision medicine tools from research environments into routine clinical practice remains limited, largely due to challenges related to model interpretability, data quality, external validation, ethical governance, and healthcare system readiness.

This Research Topic focuses on the clinical translation and real-world implementation of AI and precision medicine in respiratory and critical care settings. Its primary goal is to bridge the gap between methodological innovation and practical clinical impact, with emphasis on improving diagnostic accuracy, therapeutic personalization, and decision-support systems while ensuring safety, transparency, equity, and reproducibility.

Key objectives include evaluating the clinical validity and utility of AI-driven models and multi-omics biomarkers, assessing their impact on patient-centered outcomes and healthcare efficiency, and identifying scalable strategies for their responsible integration into diverse healthcare systems, including resource-limited settings.

We particularly welcome contributions addressing how computational and precision approaches can improve disease stratification, predict clinical trajectories, and guide individualized interventions across both communicable and non-communicable respiratory diseases. We welcome articles addressing, but not limited to, the following themes:

• AI and machine learning applications in pulmonary and intensive care medicine

• Deep learning and thoracic imaging for diagnosis and prognostication

• Large language models and clinical decision-support systems

• Digital health technologies, wearables, and remote patient monitoring

• Multi-omics integration and biomarker discovery in respiratory diseases

• Precision medicine strategies in tuberculosis, COPD, asthma, and ILD

• Predictive modeling for acute respiratory failure, sepsis, and critical illness

• Implementation science and real-world validation of AI tools

• Ethical, legal, and regulatory frameworks for AI in healthcare

• Explainable AI and equitable deployment in global respiratory care

We welcome Original Research Articles, Systematic Reviews, Meta-Analyses, Narrative Reviews, Clinical Trials, Translational Research, Brief Reports, Perspectives, Technical Reports, Case Series.