Nanostructured‐Based Optical Readouts Interfaced with Machine Learning for Identification of Extracellular Vesicles (Adv. Healthcare Mater. 5/2023). Issue 5 (17th February 2023)

• Record Type: Journal Article
• Authors: del Real Mata, Carolina; Jeanne, Olivia; Jalali, Mahsa; Lu, Yao; Mahshid, Sara
• Is Part Of: Advanced healthcare materials. Volume 12:Issue 5(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-02-17
• Subjects: Biomedical materials -- Periodicals; 610.28
• DOI: 10.1002/adhm.202370024
• Languages: English
• ISSNs: 2192-2640

Abstract

Abstract : Extracellular Vesicles Identification Extracellular vesicles (EVs) are a potential cancer biomarker enclosing molecular information that hold great promise for early‐stage diagnosis and monitoring of cancer. Novel adaptations of optical readouts integrate nanostructures to enhance the sensitivity of the detection of EVs. Furthermore, combining them with machine learning analysis can overcome common challenges in the study of EVs present in liquid biopsy samples. These topics are reviewed in article 2202123 by Sara Mahshid and co‐workers. Cover image designed by Ella Maru Studio.