Taha, Bakr Ahmed and Abdulrahm, Zahraa Mustafa and Addie, Ali J. and Haider, Adawiya J. and Alkawaz, Ali Najem and Yaqoob, Isam Ahmed M. and Arsad, Norhana (2025) Advancing optical nanosensors with artificial intelligence: A powerful tool to identify disease-specific biomarkers in multi-omics profiling. Talanta, 287. ISSN 0039-9140, DOI https://doi.org/10.1016/j.talanta.2025.127693.
Full text not available from this repository.Abstract
Multi-omics profiling integrates genomic, epigenomic, transcriptomic, and proteomic data, essential for understanding complex health and disease pathways. This review highlights the transformative potential of combining optical nanosensors with artificial intelligence (AI). It is possible to identify disease-specific biomarkers using real-time and sensitive molecular interactions. These technologies are precious for genetic, epigenetic, and proteomic changes critical to disease progression and treatment response. AI improves multi-omics profiling by analyzing large, diverse data sets and common patterns traditional methods overlook. Machine learning tools Biomarkers Discovery is revolutionizing, drug resistance is being understood, and medicine is being personalized as the combination of AI and nanosensors has advanced the detection of DNA methylation and proteomic signatures and improved our understanding of cancer, cardiovascular disease and vascular disease. Despite these advances, challenges still exist. Difficulties in integrating data sets, retaining sensors, and building scalable computing tools are the biggest obstacles. It also examines various solutions with advanced AI algorithms and innovations, including fabrication in nanosensor design. Moreover, it highlights the potential of nanosensorassisted, AI-driven multi-omics profiling to revolutionize disease diagnosis and treatment. As technology advances, these tools pave the way for faster diagnosis, more accurate treatment and improved patient outcomes, offering new hope for personalized medicine.
| Item Type: | Article |
|---|---|
| Funders: | Universiti Kebangsaan Malaysia, Ministry of Higher Education, Malaysia [Grant no. FRGS/1/2021/TK0/UKM/02/17] |
| Uncontrolled Keywords: | Multi-omics; Optical nanosensors; AI; Biomarker; Nanomaterial |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering > Department of Electrical Engineering |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 03 Oct 2025 08:13 |
| Last Modified: | 03 Oct 2025 08:13 |
| URI: | http://eprints.um.edu.my/id/eprint/47827 |
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