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Updated: May 29, 2026
04:04
Asthma Detection Research Based on Voice Signal Processing and Machine Learning
Published on: July 22, 2025
Current understanding and future directions in severe asthma through artificial intelligence-integrated multi-omic
Sundhas Rafeeq Valappil1, Mohammed Uddin1,2,3,4, Saba Al Heialy5,4
1College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai Health, Dubai, UAE.
Summary
Artificial intelligence (AI) combined with multi-omic data offers new ways to understand severe asthma. These approaches identify biomarkers and personalize treatments for better patient outcomes.
Area of Science:
- Biomedical research
- Computational biology
- Precision medicine
Background:
- Severe asthma is a complex, heterogeneous condition with persistent poor control in some patients.
- Multi-omic technologies (genomics, transcriptomics, proteomics, metabolomics) provide insights into asthma's molecular basis.
- Artificial intelligence (AI) can analyze large multi-omic datasets to reveal complex patterns.
Purpose of the Study:
- To review the role of AI-integrated multi-omic approaches in severe asthma research.
- To highlight how AI can refine disease endotypes and enable personalized treatment strategies.
- To discuss the potential of these technologies for transforming severe asthma management.
Main Methods:
- Analysis of multi-omic data (genomics, transcriptomics, proteomics, metabolomics) using AI-driven models.
- Focus on genetic loci, single-cell RNA sequencing for cellular heterogeneity, and proteomic profiles.
- Review of current literature on AI applications in asthma research.
Main Results:
- AI-driven analysis of multi-omic data can uncover patterns missed by traditional methods.
- These approaches can improve diagnostic precision and predict therapeutic responses.
- Identification of key biomarkers and differentiation of asthma phenotypes are facilitated.
Conclusions:
- AI-integrated multi-omic approaches hold significant potential for advancing severe asthma research.
- These technologies can guide the development of novel, targeted therapies for personalized medicine.
- Overcoming challenges in clinical translation is crucial for realizing the full benefits for patients.
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