About this Research Topic
The diagnosis and treatment of respiratory diseases require the integration of multi-omics information in dimensions of radionics, genomics, proteomics, metabolomics, transcriptomics, lipidomics, and more. To better assist the clinical workflow, it is imperative to further enhance the actual efficacy and repeatability of AI models, identify potential biomarkers for diagnostic and therapeutic purposes, and build multi-omics fusion algorithms to form a systematic analytic pipeline.
This Research Topic aims to promote the application of cutting-edge artificial intelligence technology and molecular biomarkers in the field of respiratory disease screening, diagnosis, treatment and prognosis. Research that successfully combines basic, translational, and patient-centered approaches are of particular interest.
This Research Topic welcomes Original Research and Review articles focusing on major trends and challenges in this field. Potential topics include, but are not limited to:
- The applications of AI in the clinical diagnosis and therapeutic strategies of respiratory diseases
- Advances in artificial intelligence algorithms for pulmonary medical imaging
- Novel diagnostic molecules and/or therapeutic biomarkers in respiratory diseases
- Multi-omics deep neural networks for respiratory disease discovery
- The effectiveness and repeatability of AI systems in the real world
Keywords: respiratory diseases, artificial intelligence, molecular biomarkers, clinical practices, multi-omics interaction
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.