Biosensors and machine learning for enhanced detection, stratification, and classification of cells: a review.
Biological cells, by definition, are the basic units which contain the fundamental molecules of life of which all living things are composed. Understanding how they function and differentiating cells from one another, therefore, is of paramount importance for disease diagnostics as well as therapeut...
| Publicado en: | Biomedical Microdevices Vol. 24; no. 3; pp. 1 - 21 |
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| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Sep2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=158629528&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 158629528 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13872176 ODN jtl: Biomedical Microdevices issn: 13872176 maglogo: N pubinfo: dt: Sep2022 vid: 24 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 158629528 10.1007/s10544-022-00627-x 158629528 ppf: 1 ppct: 20 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Biosensors and machine learning for enhanced detection, stratification, and classification of cells: a review. aug: au: Raji, Hassan Tayyab, Muhammad Sui, Jianye Mahmoodi, Seyed Reza Javanmard, Mehdi affil: Department of Electrical and Computer Engineering, Rutgers University, 08854, Piscataway, NJ, USA sug: ab: Biological cells, by definition, are the basic units which contain the fundamental molecules of life of which all living things are composed. Understanding how they function and differentiating cells from one another, therefore, is of paramount importance for disease diagnostics as well as therapeutics. Sensors focusing on the detection and stratification of cells have gained popularity as technological advancements have allowed for the miniaturization of various components inching us closer to Point-of-Care (POC) solutions with each passing day. Furthermore, Machine Learning has allowed for enhancement in the analytical capabilities of these various biosensing modalities, especially the challenging task of classification of cells into various categories using a data-driven approach rather than physics-driven. In this review, we provide an account of how Machine Learning has been applied explicitly to sensors that detect and classify cells. We also provide a comparison of how different sensing modalities and algorithms affect the classifier accuracy and the dataset size required. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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